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Our Product Vulcan is a cybersecurity solution specifically designed for GenAI, offering two core services: Red Team (vulnerability assessment) and Blue Team (real-time defense). It ensures GenAI compliance, cybersecurity robustness, and operational integrity. Since its official launch in 2024, Vulcan has been recognized by the international standard-setting organization OWASP as a certified vendor for LLM GenAI security testing and assessment. It is one of the few solutions capable of supporting multiple Asian languages (Traditional Chinese, Simplified Chinese, Japanese, Korean, Thai) and Standard Arabic.Learn more about us 👉 Vulcan product: https://vulcanlab.ai/Vulcan LinkedIn: https://www.linkedin.com/company/vulcanlab-ai/AIFT group: https://aift.io/Tech Blog: https://medium.com/onedegree-tech-blogAbout the roleWe are looking for a talented Machine Learning Engineer to join our Product Core Engineering team. You will be responsible for building and optimizing machine learning workflows that directly power our AI-driven products. This role focuses on the full lifecycle of model development — from training and fine-tuning to deployment and monitoring — ensuring robust and efficient ML systems at scale. Why Join Us?Product Impact: Your work will be directly embedded in our core AI products, shaping user experience and product capabilities.Engineering Excellence: Be part of a team that values high-quality engineering, reproducibility, and scalability.Innovation: Opportunity to experiment with cutting-edge ML and GenAI technologies in production settings.Collaboration: Work alongside backend, platform, and product teams in a highly collaborative environment.Competitive Package: Receive attractive compensation and benefits aligned with your skills and performance. Key Responsibilities Model Development: Design and implement training processes for machine learning classifiers and generative models.Fine-tuning Prompting: Adapt pre-trained models to specific product needs through fine-tuning, prompt engineering, and parameter optimization.Hyperparameter Management: Configure and tune hyperparameters to balance accuracy, robustness, and performance.Pipeline Engineering: Build scalable training and evaluation pipelines to support continuous experimentation.Integration: Collaborate with backend and product engineers to deploy models into production systems.Monitoring Maintenance: Establish monitoring metrics and retraining strategies to maintain model performance in dynamic environments. -

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.The Team and Role:As an Audio ML Engineer on the Logitech Hardware Audio ML and DSP Product team, you will be instrumental in developing Embedded Audio ML models that create innovative audio experiences for our customers [ e.g. Speech/Audio enhancement] . This role offers a significant opportunity to contribute directly to the audio products we develop.The Audio ML Engineers key responsibilities include:Develop production-ready Audio ML models, leveraging multi-sensor data from the product.Ensure these models are deployed for efficient inference on resource-constrained platforms by employing optimization techniques, including Post-Training Quantization (PTQ), Quantization-Aware Training (QAT), pruning etc.Your Contribution:Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will:Develop and implement highly optimized Audio ML models for efficient deployment on resource-constrained embedded platforms (e.g., ARM, Tensilica DSP, RISC-V, NPUs).Utilize techniques like  quantization [PTQ and QAT], and pruning to ensure effective on-device inference.Architect, optimize, and improve algorithm performance in complex real-world audio environments.Propose and implement novel solutions to challenging technical problems.Collaborate with various product teams to guarantee a premium and seamless customer audio experience.Key Qualifications:For consideration, you must bring the following minimum skills and experiences to our team:Audio ML Expertise (3 Years): Hands-on experience across the entire Audio ML lifecycle, including model training, tuning, quantization (PTQ and QAT), and deployment to production.ML Framework Proficiency: Advanced skills in ML frameworks (e.g., TensorFlow, Keras,PyTorch) with a history of successfully shipping Production ready Audio ML models.Embedded Optimization: Demonstrated success in optimizing model inference performance specifically for resource-constrained embedded systems.Strong Programming Best Practices: Excellent programming skills in Python and C, coupled with experience in code optimization and adherence to rigorous software best practices.Audio Data Augmentation: Experience with audio data augmentation techniques, including the ability to design, implement, and evaluate custom augmentation pipelines.ML Stack Debugging: Proficiency in Linux-based compute environments and experience debugging common ML training stack issues (e.g., OOM issues, CUDA errors, library conflicts).Preferred Qualifications:Audio Quality Assessment: Proven experience in designing and executing both subjective and objective audio quality evaluation protocols, including familiarity with industry-standard audio measurement metrics.Audio Artifact Resolution: Demonstrated track record of effectively identifying and resolving audio artifacts within ML audio chains..Technical Leadership Communication: Excellent communication, documentation, and leadership abilities, particularly in cross-functional technical environments.Initiative Execution: Highly driven individual with a demonstrated ability to deliver results and lead technically, both independently and as a contributing team member.Education:Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or a closely related field.Equivalent practical experience is considered; advanced degrees or continuing education in audio ML are highly valued.#LI-SL1Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at 1-510-713-4866 for assistance and we will get back to you as soon as possible.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.The Role :In this role you will be part of the Logitech Hardware Audio DSP and ML team developing and will be implementing real-time audio ML solutions to deliver innovative audio experiences to the customer. If you have a strong understanding of Audio DSP and TinyML  apply for this role and have a huge contribution on the audio products that we develop!Your Contribution:Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech.In this role you will:Responsible for developing model and inference on resource constrained platforms like Tensilica DSP, ARM and RISCV cores.Responsible for optimizing and improving algorithm performance in real-world conditions – demonstrating innovative solutions to tough challenges.Work with cross-functional product team to deliver seamless customer audio experience.Key Qualifications:For consideration, you must bring the following minimum skills and experiences to our team:7 years of experience working in audio signal processing product teams.Tiny ML / Embedded ML - Hands-on experience porting neural network algorithms from intermediate representations such as Tensor Flow (TFLM), ONNX, etc. onto embedded targets using device-specific compilation tools and/or inference API’s.Deep understanding of on-device quantization techniques including post-training quantization, training-aware quantization, mixed precision inference.Strong programming skills in c, python.Conceptual understanding of how neural network operators map to embedded hardware accelerators such as DSP’s and NPU’s.Familiarity with Deep Learning Audio Signal Processing approaches for tasks including Speech enhancement / noise suppression / voice pickupAdditional Skills:Experienced with Linux, Docker.Familiarity with CMSIS NN, HIFI NNLib is a plusFamiliarity with audio measurements and standard subjective/objective audio evaluation metrics.Experience working in hardware product teams from product concept to mass productionGood Audio listening skills and experience detecting audio artifacts.Experience communicating effectively in a cross functional environment. Strong problem-solving, critical-thinking skillsFamiliarity with code version control practicesEducation:Minimum Engineering degree in EE, CS or equivalent practical experience. #LI-MR2Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at 1-510-713-4866 for assistance and we will get back to you as soon as possible.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.The Team and Role:As an Audio ML Data Engineer on the Logitech Hardware Audio ML and DSP Product team, you will work on developing and managing our audio datasets and data pipelines. This work directly influences the innovative audio experiences we deliver to our customers.The Audio ML Data Engineers key responsibilities include:Data Pipeline Management: Ensuring the integrity and quality of Audio ML data pipelines and datasets, which involves robust data augmentation and managing workflows for supervised, unsupervised, and semi-supervised ML audio applications.Model Development and Deployment: Collaborating with the team to develop and deploy Audio ML models, specifically targeting platforms with strict resource limitations (such as Tensilica DSP, ARM, and RISC-V).Your Contribution:Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will:Design and manage audio data collection, curation, labeling, cleaning and augmentation pipelinesEvaluate and implement scalable data augmentation techniques.Establish and maintain high-quality, well-versioned, and documented datasets essential for training, validation, and benchmarking of audio ML models.Build automated tools for monitoring and ensuring the quality and statistical diversity of audio data.Formulate and execute strategies for continuous improvement of existing datasets.Key Qualifications:For consideration, you must bring the following minimum skills and experiences to our team:Audio Data Expertise: A minimum of 3 years of direct experience working with extensive audio datasets, including advanced data augmentation and preprocessing techniques audio ML.Python Proficiency: Strong proficiency in Python for both ML model development and automating data pipelines.Data Pipelines and ML Frameworks: Proven expertise in building scalable data pipelines and expertise in employing ML frameworks (TensorFlow, Keras) with large-scale, complex datasetsPreferred Qualifications:​Expert-level skills in audio analysis, including listening and artifact detection, with a proven track record of validating performance across diverse datasets.Strong familiarity with designing, executing, and statistically analyzing audio quality measurement protocols, specializing in managing data-driven objective and subjective evaluations.A strong data-first mindset, with a demonstrated ability to drive innovation both independently and as part of a team.Proficiency in C and SQL, along with experience using code version control systems (Git), is a valuable asset.Excellent cross-functional communication, documentation, and leadership skills, emphasizing transparency in data and results.Education:Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or a related discipline.Equivalent practical experience in professional audio ML and data engineering considered; advanced/relevant continuing education preferred.#LI-SL1Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at 1-510-713-4866 for assistance and we will get back to you as soon as possible.

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. Preferred qualifications: Master's degree or PhD in Computer Science or related technical fields. 2 years of experience with data structures and algorithms. Experience developing accessible technologies. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. We are the team that builds Google Tensor - Google’s custom System-on-Chip (SoC) that powers the latest Pixel phones. Tensor makes transformative user experiences possible with the help of Machine Learning (ML) running on the Tensor TPU.As a Software Engineer you will work on developing ML compilers for the Tensor TPU to accelerate Generative AI and other complex machine learning models running on custom hardware accelerators. Along with your technical expertise, you will manage project priorities, deadlines and deliverables.The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.Responsibilities Write product or system development code. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Triage and root-cause correctness and performance issues encountered while enabling ML models on EdgeTPU. Propose and implement fixes to the compiler to address these issues in collaboration with other compiler engineers. Interact closely with model owners to influence their model architectures to make them run efficiently on the EdgeTPU. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field. 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. 5 years of experience in developing machine learning models such as recommender systems, pricing optimization, user modeling, or computational advertising. Experience in architecting and deploying ML systems that functions efficiently at a massive scale. Experience mentoring and leading engineers on technical projects. Understanding of large-scale data processing frameworks such as SQL, Spark or MapReduce, Python for efficient data querying and analysis. Excellent communication skills with the ability to convey the team's technical goal effectively to executive leadership and cross-functional stakeholders. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. Google Photos is a photo sharing and storage service developed by Google. Photos is one of the most sought after products at Google and is looking for both client-side (web and mobile), with server-side (search, storage, serving) and machine intelligence (learning, computer vision) Software Engineers. We are dedicated to making Google experiences centered around the user.Responsibilities Establish and lead the long-term technical goal for Machine Learning (ML) powered personalization, pricing and recommendation systems that scale to billions of users. Design, develop and scale production-grade ML systems with an emphasis on performance, reliability, debuggability and model explainability. Serve as a technical pillar for the team by mentoring engineers, fostering their growth, providing design guidance and cultivating a culture of engineering excellence. Identify machine learning applications to drive user growth, engagement, and business, while leading modeling initiatives from exploring novel algorithmic approaches for offer optimization to developing models for new product tiers. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience in Machine Learning, Multimodal Machine Learning, Large Language Model, Machine Learning Infrastructure. Preferred qualifications: 5 years of experience in Machine Learning, LLM and GenAI. Experience architecting and launching ML systems that operate at a massive scale. Experience with modern deep learning architectures and frameworks with an understanding of machine learning fundamentals. Ability to influence cross-functional leaders, and work effectively across different teams to drive adoption of AI-first practice with excellent collaboration and communication skills. Passionate for building excellent products. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. Play Games offers cross-game identity and profile, access to titles, achievements, leaderboards, and rewards. We are 500M Monthly Active Users (MAU) products and are integrated into the biggest mobile games on Android. Play Games Services is a critical component of a renewed focus on Play as a gaming platform.Google Play offers music, movies, books, apps and games for devices, powered by the cloud. It syncs across devices and on the web. As part of the Android and Mobile team, Googlers working on Google Play do everything from engineering our backend systems, to shaping product strategy, to forming great content partnerships. They make it possible for people to do things like buy an ebook or song on their Android phone, then have it instantly available on their laptop. The Google Play team enhances the Android ecosystem by giving developers and partners a premium store where they can reach millions of users.Responsibilities Define the gaol and technical strategy for applying Machine learning technologies especially multimodal and advanced models like LLMs to create and scale high-impact, AI-assisted in-game experiences that drive growth and engagement. Drive the end-to-end research process, from defining problems, scoping, prototyping solutions, publishing results, and partnering with product teams to ship AI-enabled features. Apply deep domain expertise to build and deploy new advances in multimodal understanding and generative AI. Build cross-Product Area collaboration with Google Deepmind (GDM) to bring model applications for our use cases. Define the infrastructure for computing and serving quality signals. Define, establish, and track key performance indicators and metrics to evaluate and iterate on the quality of our ML systems. Work collaboratively with _storiesArea Technicall Leads, Technical leads and other engineers in cross-functional teams and help align the AI evolution. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. 1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential selection), ML infrastructure, or specialization in a related ML field. 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging). Experience in Python, machine learning, data analytics. Preferred qualifications: Master's degree or PhD in Computer Science or a related technical field. 2 years of experience with data structures and algorithms. Experience in developing accessible technologies. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. Team is responsible for Content Trust Platform which includes Machine Learning (ML) models, infrastructure, rules, tools and workflows that auto-moderate user-generated content on Google Maps like ensuring quality of user-generated content, prevent fraud and abuse, protecting Google Maps from certain issues.The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives.The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.Responsibilities Write product or system development code. Collaborate with peers and stakeholders through design and code reviews to ensure best practices among available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality. Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience building and developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture. 5 years of experience in a people management or team leadership role. Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field. Experience leading infrastructure teams through major technological shifts or platform migrations. Experience in areas such as distributed systems, performance optimization and reliability engineering. Ability to influence and align priorities across leaders. Excellent communication and stakeholder management skills. Passion for addressing ambiguous, open-ended problems with the ability to build and execute a clear path forward. About the jobLike Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.Responsibilities Impact the reliability, speed, and efficiency of Google Search's AI-powered experiences. Lead a team building the ML infrastructure that powers Search, guiding technical direction and long-term evolution. Provide the clarity, context, and support your team needs to solve problems and deliver durable solutions. Help the team navigate ambiguity and scale ideas from concept to production. Invest in team growth and well-being, building an environment where talented engineers can do their work. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google welcomes people with disabilities.Minimum qualifications: Bachelor’s degree or equivalent practical experience. 2 years of experience with software development in Python, C++ or Java, or 1 year of experience with an advanced degree. Preferred qualifications: Master's degree or PhD in Computer Science or a related technical field. 2 years of experience with data structures or algorithms. Experience with Generative AI, Large Language Models (LLM), or Machine Learning infrastructure, including model deployment, performance optimization, profiling, and debugging. Experience with distributed computing leveraging GPUs or TPUs, and cloud services in the areas of compute, storage, or networking. Ability to grow in a changing environment where Artificial Intelligence (AI) technologies are advancing. Ability to collaborate with cross-functional teams. About the jobGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Measure and optimize AI/ML model performance on Google Cloud infrastructure. Identify and resolve performance bottlenecks, collaborating with internal infrastructure teams to enhance support for demanding AI workloads as needed. Develop and deliver high-quality training and demos for both customers and internal teams. Contribute to ongoing product improvement by identifying bugs, recommending enhancements, and writing and testing production-quality code. Conduct in-depth performance profiling, debugging, and troubleshooting of training and inference workloads, ensuring adherence to best practices through design and code reviews. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.