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Responsibilities1. Develop and implement machine learning algorithms and collaborated with cross-function teams, including product, backend teams, and domain experts to optimize clinical and diagnosis workflow. 2. Deploy machine learning algorithms to aetherAI products, including the web-based platform and edge devices. 3. Engage in medical imaging research using machine learning techniques with physicians and teams to solve real-world problems.Minimum Qualifications 1. Experience in machine learning, data mining, statistical modeling, and software design. 2. Fluent in Python programming, including general packages such as NumPy, and deep learning frameworks such as TensorFlow / PyTorch. 3. Familiarity with Linux/Unix environments, Docker, and Git. 4. Good communication and presentation skills.

AI Engineer with full-stack capabilities in Computer Vision and NLP, supporting the building, testing, and deployment of machine learning models and algorithms. The role works closely with senior engineers and cross-functional teams (product, marketing, data science) to integrate AI features into user-facing products and internal tools. Responsibilities also include improving AI pipeline performance, monitoring and evaluating deployed AI systems in operation, and assisting in the development of AI-powered internal tools such as assistant bots for content generation, marketing workflows, and other internal processes.Mô tả công việcDevelop and test AI-driven features in collaboration with the senior engineering team, focusing on marketing tools, user engagement, and automation products.Assist in building and improving internal AI tools, such as bots for content generation and workflow automation, to enhance team productivity.Support the deployment and maintenance of machine learning models and ensure their effectiveness in production environments.Continuously monitor AI systems and suggest improvements based on user feedback and system performance.Work in an agile environment, participating in sprint planning, development, and testing cycles.Yêu cầu công việcBachelor’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related field.Basic understanding of AI/ML concepts and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.Proficiency in programming languages like Python, with a solid understanding of coding practices and principles.Familiarity with data manipulation and analysis tools (e.g., Pandas, NumPy).Familiarity with cloud platforms (AWS, GCP, Azure) is a plus.Strong analytical and problem-solving skills, with a willingness to learn and adapt to new technologies and challenges.Good communication skills and the ability to work collaboratively within a teamExperience with project about Computer vision and NLP

The Senior Lead Storage and Server Test Engineer will play a pivotal role in the design, development, and execution of comprehensive test strategies for our AI data center's storage and server infrastructure. This leadership position requires deep expertise in enterprise storage systems, server architectures, networking, and a strong understanding of the unique performance and reliability demands of AI/ML workloads. The ideal candidate will be a hands-on technical leader, capable of mentoring junior engineers, driving test automation, and collaborating across engineering teams to deliver robust and high-performing solutions.Required Qualifications• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical field.• 3+ years of experience in hardware and/or software testing, with at least 5 years focused on enterprise-level storage and server systems.• Proven experience in a lead or senior technical role, mentoring and guiding other engineers.• Deep expertise in various storage technologies including NVMe, SAS/SATA SSDs/HDDs, RAID, distributed file systems (e.g., Ceph, Lustre, GPFS), SAN, and NAS.• Strong understanding of server architectures (x86, ARM, GPU servers), CPU/memory subsystems, PCIe, and power management.• Strong understanding of server architectures (x86, ARM, GPU servers), CPU/memory subsystems, PCIe, power management, and Baseband Management Controllers (BMC) functionality.• Proficiency in scripting languages (e.g., Python, Bash) for test automation and data analysis.• Experience with Linux operating systems (e.g., Ubuntu, CentOS, RHEL) and command-line tools.• Familiarity with networking concepts (Ethernet, TCP/IP, InfiniBand) and network testing methodologies.• Experience with test methodologies such as performance testing, reliability testing, stress testing, and fault injection.• Excellent problem-solving, analytical, and debugging skills.• Strong communication and interpersonal skills, with the ability to collaborate effectively across diverse teams.Preferred Qualifications• Familiarity with OCP (Open Compute Project)• Experience with cloud environments (AWS, Azure, GCP) and virtualization technologies.• Knowledge of containerization technologies (Docker, Kubernetes).• Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) and their infrastructure requirements.• Experience with performance profiling tools (e.g., fio, Iometer, Perf, VTune).• Contributions to open-source projects related to storage, servers, or testing.• Certifications in relevant technologies (e.g., NetApp, Dell EMC, HPE, NVIDIA).

Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at www.asteralabs.com.Job Description Astera labs is seeking a skilled and motivated Data Scientist. This individual will play a pivotal role in identifying key data points for collection, developing strategies to accumulate data and deriving actionable insights an anomaly based on a solid foundation of relevant know-how. Also, will also be responsible for creating, testing, and deploying scripts and methods for data collection and analysis to support decision-making. The Engineer will collaborate with cross-functional teams to identify critical data sources to determine the most effective data collection strategies, will develop automated and scalable data collection pipelines, will ensure data quality, integrity, and consistency across all sources and may use AI techniques to refine the results toward failures predictions. Basic Qualifications Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, or a related field. Advanced degrees in data science or Machine learning / AI - Advance. Proficiency in programming languages such as Python, R, or MATLAB. Strong understanding of data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Understanding of high speed interfaces such as Ethernet, PCI-E , WiFi. Experience with data visualization tools such as Tableau, Matplotlib, Graphana. Strong analytical and critical-thinking skills to identify patterns and outliers. Customer-obsession, Think and act with the customer in mind! Goal-driven, Self-motivated, be able to work independently and with teams with people around the globe. Entrepreneurial, open-minded behavior and can-do attitude. Required Experience Experience with data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Machine learning and AI techniques and frameworks (e.g., TensorFlow, Scikit-learn). Proven ability to manage multiple tasks and meet deadlines. Preferred Experience Embedded Firmware development with C-language, scripting with Python or other equivalent programming languages. Master’s degree in a relevant field. Experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing. Familiarity with big data technologies (e.g., Hadoop, Spark). Knowledge of engineering design tools and processes. We know that creativity and innovation happen more often when teams include diverse ideas, backgrounds, and experiences, and we actively encourage everyone with relevant experience to apply, including people of color, LGBTQ+ and non-binary people, veterans, parents, and individuals with disabilities.

At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google’s technology, platforms and people and we welcome Indigenous applicants. Please see our Reconciliation Action Plan for more information.Minimum qualifications: PhD degree in Computer Science, a related field, or equivalent practical experience. One or more scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.). Preferred qualifications: Experience in areas like face anti-spoofing, biometrics, 3D/2.5D vision, facial landmark/pose estimation. Experience with TensorFlow, Flume, common computer vision libraries/frameworks and Android. Interest to build production systems. Excellent software engineering skills (e.g., C++, python, data processing, production backend development, etc.). About the jobAs an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. In this role, you will develop models and architectures grounded in foundation models, data-efficient algorithms, and federated learning.Responsibilities Author research papers to share and generate impact of research results across the team and in the research community. Help in growing research business across teams by sharing research trends and best practices within the community. Define the data structure, framework, design, and evaluation metrics for research solution development and implementation under minimal guidance. Identify timelines and obtain resources needed. Identify new and upcoming research areas by interacting with external and internal collaborators. Help in developing research strategy and plans to expand the impact of Google research with some guidance. Contribute to conducting experiments based on the research question. Develop research prototypes or conduct simulations to further evaluate the impact of research, finalize hypotheses, and refine the research methodology under minimal guidance. 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 in Computer Science, Mathematics, a related field, or equivalent practical experience. 1 year of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume). Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript. Experience managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams. Preferred qualifications: Experience working with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. Experience working with Big Data, information retrieval, data mining, or machine learning. Experience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow). Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments. About the jobAs a Data Engineer for the Enterprise Platforms team, you will play a vital role in building and maintaining the data infrastructure that fuels our product strategy. You will design, develop, and optimize data pipelines, ensuring data quality and accessibility for advanced analytics. Your technical expertise will enable the product team to leverage data-driven insights to optimize product feature adoption and performance and measure the impact of strategic initiatives. To accelerate the growth and market leadership of Enterprise Buying Platforms (DV360 and SA360), you will answer critical business questions and deliver actionable, data-driven insights that inform product and commercial strategy. The Enterprise Platform Data Science team provides quantitative support, market understanding and a strategic perspective to our partners throughout the organization, in close collaboration with the Ads Commerce Finance team.Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale. Responsibilities Create and deliver best practice recommendations, tutorials, blog articles, sample code, and technical presentations, tailoring approach and messaging to varied levels of business and technical stakeholders. Design, develop, and maintain scalable and reliable data pipelines to collect, process, and store data from various data sources. Implement robust data quality checks and monitoring to ensure data accuracy and integrity. Collaborate with cross-functional teams (data science, engineering, product managers, sales and finance) to understand data requirements and deliver impactful data solutions. Optimize data infrastructure for performance, efficiency, and scalability to meet evolving business needs. 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. 5 years of experience with software development in one or more programming languages. 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture. Preferred qualifications: Experience working with data science tools such as Jupyter notebooks, Open Telemetry, JMX and other monitoring solutions. Experience with Database optimizations - query and executor optimizations and Data lakes like Apache Iceberg, Apache Hudi, Delta lake, etc. Experience with OSS projects like Spark, Hive, Trino and in benchmarking and building custom benchmarks. Experience in developing Cloud or SaaS 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. Join the Google Cloud Dataproc team and build the next generation of data processing, combining the best of open source with Google's innovation. We are not just managing Apache Spark and Hadoop clusters; we are fundamentally accelerating big data. For engineers passionate about the future of data, you will be building an AI/ML-ready platform, leveraging native GPU support and specialized run times pre-packaged with PyTorch, TensorFlow, and RAPIDS, integrated with Vertex AI for ML Operations. This is where you architect the unified, open lake house of tomorrow, seamlessly connecting with formats like Apache Iceberg, Delta, Hudi and providing enterprise-grade security and scale that empowers the world's most demanding data scientists and engineers.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 Lead the development of next-generation features, positioning Cloud Dataproc as the preferred platform for Spark, Flink, Trino, and emerging cloud technologies. Define the road map for enhancing open-source technologies like Spark, Hive, Trino, Iceberg, Hudi, and Delta into Dataproc. Drive the design and implementation of Data Lakes and Lake Houses, including Apache Iceberg and Hudi along with ehnancing the performance and efficiency of open-source technologies within the platform. Develop and implement software solutions leveraging Google technologies for accelerated cluster setup, streamlined operations, and monitoring. Establish benchmarks to identify and resolve performance bottlenecks, ensuring Spark job certification. 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 in Computer Science, Data Science, a related field, or equivalent practical experience. 6 years of experience as a technical sales engineer in AI/ML, or in a software engineering role. Experience in Python and Machine learning frameworks (e.g., TensorFlow, PyTorch). Experience delivering technical presentations and leading business value sessions. Experience in Generative AI as a developer. Ability to communicate in English and Korean fluently as this is a customer-facing role that requires interactions with the local stakeholders. Preferred qualifications: Experience in designing and deploying multi-agent architectures with Agent Development Kit (ADK), and integrating next-gen Generative AI models (e.g., Gemini, Imagen, Veo) to build dynamic applications. Experience with core search concepts like indexing and query rewriting. Experience in systems design with the ability to architect and explain data pipelines, ML pipelines, and ML training and serving approaches. Understanding of implementation and optimized Retrieval-Augmented Generation (RAG) models using both first-party and open-source models. Ability to travel up to 20% of the time. About the jobIn this role, you will support Google Cloud Sales and Engineering teams to incubate, pilot, and deploy Google Cloud’s Artificial Intelligence/Machine Learning (AI/ML) and Generative AI technology with AI native customers, large enterprises, and early-stage AI startups. You will help customers innovate faster with solutions using Google Cloud’s flexible and open infrastructure including AI Accelerators Tensor Processing Unit/Graphics Processing Unit (TPU/GPU). You will identify, assess, and develop GenAI and AI/ML applications by applying key industry tools, techniques, and methodologies to solve problems. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and help to analyze cost to performance. You will work with internal Cloud AI teams to remove roadblocks and shape the future of offerings.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 Advise customers by understanding their business processes and objectives. Architect AI-driven solutions spanning Data, AI, and Infrastructure, and work with peers to include the full cloud stack in the overall architecture. Work with customers on application prototypes, demonstrating Generative AI features, prompting and tuning models, optimizing model performance, profiling, benchmarking, and troubleshooting to find solutions to issues in Generative AI applications. Build repeatable technical assets such as scripts, templates, reference architectures, to enable other customers and internal teams. Coordinate regional field enablement with leadership and work with product and partner organizations on external enablement activities. Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and Artificial Intelligence/Machine Learning (AI/ML) by advocating for enterprise customer requirements. 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.

This role requires you to work in a shift pattern or non-standard work hours as required. This may include weekend work.Minimum qualifications: Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 6 years of experience with writing code in one or more general purpose programming languages (e.g., C++, Java, Python, Go, etc). Experience with Linux/Unix systems with debugging issues across the hardware/software boundary on enterprise-grade server infrastructure. Experience in troubleshooting for customer needs, and triaging technical issues across the stack (e.g., hardware faults, networking, virtualization, kernel drivers, firmware, performance). Preferred qualifications: Experience in working with distributed systems with the knowledge of common solutions, design patterns, or best practices. Experience in working with Artificial Intelligence/Machine Learning (AI/ML) computing hardware, including Graphics Processing Unit (GPUs) or other accelerators. Experience with containerization and orchestration technologies like Kubernetes or Slurm. Experience with ML frameworks (e.g., TensorFlow, Pytorch), with the knowledge of the AI/ML training and inference lifecycle. Excellent troubleshooting and communication skills with attention to details. About the jobThe Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate. In this role, you will own customer issues and provide specialized support to other teams. You will be a part of a global team that provides support to ensure customers can deploy their Artificial Intelligence (AI) and Machine Learning (ML) workloads on AI Infrastructure products. You will troubleshoot technical problems with hardware and software debugging, networking, Linux system administration, coding/scripting, and updating documentation. You will help the customer’s success in the AI/ML space by making improvements to the product, internal tools, processes, and documentation. You will help drive business growth by recognizing and advocating for the customers’ tests related to AI deployments.Responsibilities Manage customer’s problems through diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on AI/ML infrastructure. Develop an understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the root cause for customer reported issues, and building tools for diagnosis. Act as a consultant and subject matter expert for internal stakeholders in Engineering, Business, and customer organizations to resolve deployment and operational obstacles in AI infrastructure environments. Work with multiple Product and Engineering teams to find ways to improve the product, and interact with our Site Reliability Engineering (SRE) teams to drive production. Be available for non-standard work hours or shifts which may include weekends as needed. 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.

To start the application process, you will need an updated CV or resume and a current unofficial or official transcript in English. Click on the “Apply” button on this page and provide the required materials in the appropriate sections (PDFs preferred):In the “Resume Section:” attach an updated CV or resume. Please ensure you include the following in it, all consolidated in a single PDF:Research work: Projects, Publications, Research experience and References (if any)Statement of purpose (no more than 500 words), detailing reasons for your interest in the Post-Doctoral Researcher role. Please ensure you’ve listed your graduation date (in MM/YY) In the “Education Section:” attach a current or recent unofficial or official transcript in English. Under “Degree Status,” select “Now attending/Graduated” to upload a transcript.If you think this role interests you, please apply to this role.Minimum qualifications: PhD degree in a STEM field (e.g., Computer Science, Mathematics, or Statistics) or equivalent practical experience. Experience with one or more general purpose programming languages: Python, C/C++, or Java, etc. and training deep learning models in frameworks such as JAX, TensorFlow, or PyTorch. Research experience in machine learning or AI techniques (e.g., open source project(s), campus lab experience, research internship(s), or publication(s)). One or more scientific publication submission(s) in AI conferences (e.g., NeurIPS, CVPR, ICCV, ICLR). Preferred qualifications: Master’s degree in a STEM field (e.g., Computer Science, Mathematics, or Statistics), or equivalent practical experience. Ability to work and collaborate across multiple teams and work with ambiguity. About the jobThe Post-doctoral Researcher role is a 12 to 24-month role designed to give you industry experience working on challenging problems together with Google DeepMind India scientists and engineers in India.As a Post-Doctoral Researcher, you will collaborate with researchers, scientists, and engineers at Google DeepMind India working on fundamental research and applied problems in a wide range of areas in Computing. You will have a wide range of opportunities ranging from conducting fundamental research and exploring their applications in products and services used by billions of people, and conducting research that contributes to human-centered AI and catalyzes AI for social good.Google DeepMind India addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field we publish regularly in top-tier conferences,academic journals, release projects as open source, and apply research to Google products.Responsibilities Work with research mentors to formulate research projects or novel applications of machine learning aligned with the team's mission. Conduct research and publish high quality work. Design and execute large-scale experiments, writing high-quality, reusable code, and contributing to a production-ready system using frameworks such as JAX. Learn and understand research in machine learning algorithms. Understand how to use research to drive design decisions. 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.