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公司介紹 這是一家深耕台灣市場、具高度用戶滲透率的 FinTech 科技公司，長期處於高流量、高交易頻率的業務場景。產品服務已融入日常生活與金融行為，資料規模與複雜度持續成長。 目前公司正進入 數據基礎建設與治理升級的關鍵階段，高層明確將「數據驅動決策」視為下一階段成長核心，並投入資源打造更穩定、可擴展的資料平台，讓數據真正成為產品與營運的決策引擎。 這個角色將站在 公司級數據戰略中心，不只是管理團隊，而是實際參與並影響整體商業方向。 工作內容 帶領資料應用部門（資料工程、資料分析、BI / Data Science 團隊），管理約 5–10 位成員 規劃並推動 公司級 Data Platform（Data Lake / DWH / ETL / Streaming） 與工程與系統架構團隊協作，確保資料系統的 穩定性、可用性與擴展性 審視並優化資料流、事件系統、Schema 與整體資料架構設計 建立 資料治理、品質控管、權限與統計口徑制度 建構指標、Dashboard 與分析框架，支援 產品、營運、行銷與管理決策 推動 A/B Test、數據實驗與行為分析，讓決策有數據依據 作為跨部門橋樑，協調技術與商業需求，推動策略落地 使用的技術 Data Platform：Data Lake、Data Warehouse、ETL / ELT、Streaming Big Data / Pipeline：Spark、Kafka、Airflow Data Ops：Pipeline 監控、版本控管、CI/CD Cloud / Hybrid：BigQuery、Snowflake（地端為主、雲端為輔） BI / Analytics：指標設計、Dashboard、實驗分析

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 in Computer Science, Mathematics, a related field, or equivalent practical experience. 3 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, and 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 applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow). Experience architecting, developing software, or production-grade Big Data solutions in virtualized environments. About the jobAs a Data Engineer for the Analytics, Insights and Measurement (AIM) team, you will Help customers, grow their businesses through trusted analytics, insights and measurement that ensure user privacy.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 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 reliable data pipelines to collect, process, and store data from various data sources. Implement 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 data solutions. Enhance data infrastructure for performance, efficiency 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.

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.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sydney NSW, Australia; Melbourne VIC, Australia.Minimum qualifications: Bachelor's degree or equivalent practical experience. 10 years of experience in software engineering, software infrastructure engineering, security, big data and analytics, cloud computing, or cloud networking. Experience with infrastructure, storage, platforms and data, as well as the cloud market and customer buying behavior. Experience engaging with, and presenting to, technical stakeholders and executive leaders. Preferred qualifications: Experience in technical sales or consulting in cloud computing, data analytics, and big data. Experience with architecture design, implementing, tuning, schema design and query optimization of scalable and distributed systems. Experience with developing data warehousing, data lakes, batch/real-time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization tools, and data governance on cloud native architectures. Understanding of customer requirements with the ability to break down requirements and design technical architectures. About the jobWhen leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. As a Practice Customer Engineer (CE) with a specialty in Data Analytics, you will partner with technical sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads. You will leverage your deep expertise in our most strategic product areas, in partnership with Platform CEs, to perform designing of data foundation architectures and develop MVPs (Minimum Viable Products) to promote new, highly specialized solutions to customers. You will solve analytics-centered customer challenges and provide a critical feedback loop to unblock customers and influence product development. You will leverage excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud.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 Drive the technical win for complex workloads within data analytics to ensure rapid and successful adoption, primarily supporting the business cycle from use case identification, technical evaluation, and through customer ramp. Combine business strategies, development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts. Provide deep technical consultation to customers, acting as a technical advisor and building lasting customer relationships. Leverage learnings from customer engagements to contribute to reusable solutions and assets with the Go-To-Market team. Provide critical feedback from customer engagements to Product and Engineering teams to improve architectures and solutions. Work within product and engineering management systems to document, prioritize and drive resolution of customer feature requests and issues. 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.

MoMo is the market leader in mobile payments in Vietnam, driven by a commitment to enhancing the lives of Vietnamese citizens through technological innovation.Within the MoMo BigData AI department, we prioritize Smart, Efficient, and Excellent execution. We are currently undergoing a major transformation to build a new hybrid data platform spanning multiple cloud vendors (GCP AWS).We are seeking an experienced Data Engineer to help us architect this platform to optimize for both budget control and technological flexibility. You will play a pivotal role in shifting our mindset from "managing data" to creating valuable Data Products that empower our internal consumers.Mô tả công việcWith MoMo's AI-first mission, we are designing and building a self-serve data platform to empower both internal teams and external partners. This platform allocates resources based on users’ needs to support:Ingesting data from diverse sources — either in batch or streaming, using both pull and push mechanismsDeveloping and deploying resilient data pipelines across the data lake, data warehouse, and streaming systemsDelivering high-quality, derived datasets to downstream tools such as BI solutions (e.g., Apache Superset,Looker Data Studio), via multiple delivery methods including APIs, datasets, and streaming dataMonitoring data quality throughout all data pipelines in the platform to ensure high-quality data, resulting in better decision-making, accurate reporting, and reliable machine learning outputsTracking and optimising resource usage for efficiencyAdditionally, we are building Data Management Systems that enable the Data Governance team and data consumers to:Manage the full data lifecycle within the big data platformExplore the MoMo data ecosystem independentlyProvide a single source of truth with high data quality to downstream consumersTrack and manage infrastructure costs across major projects, teams, and departmentsYêu cầu công việcThe MindsetPassion for Data: You dream in SQL ("SELECT COUNT(SHEEP)...") and care deeply about data accuracy.Product Thinking: You view data as a product, focusing on the usability and reliability of what you deliver to stakeholders.The Tech StackStrong Coding Skills: Proficiency in Java/Kotlin (for robust backend services) and Python (for data processing/scripting).Hybrid Cloud Infrastructure: Hands-on experience with GCP. Proficiency in Kubernetes, Docker, and IaC tools like Pulumi or Terraform.Big Data Engines: Deep understanding of computing engines like Spark, Trino, BigQuery, and Clickhouse.Orchestration: Experience building DAGs and workflows in Airflow or Temporal.Data Sources: Familiarity with diverse sources including App Events, CDC from transactional DBs (Oracle, MySQL, MSSQL), and streaming systems (Kafka, PubSub).Soft SkillsStrong problem-solving abilities with a focus on root-cause analysis.Collaborative spirit: You can explain complex infrastructure decisions to non-technical stakeholders.

MoMo is the leading mobile payments provider in Vietnam, committed to improving the lives of every Vietnamese through technological innovation. As our business continues to expand, we're looking for an experienced Data Engineer to join our Data Platform team.At MoMo, we emphasize smart, efficient, and excellent execution, with a strong focus on data quality. Our data platform delivers critical insights for:Business and app performance monitoringMachine learning products including recommendation systems, personalization, risk scoring, fraud detection, targeted promotions, and financial servicesWe're also building a next-generation hybrid data platform across multiple cloud providers, giving us greater control over both cost and technologyMô tả công việcWith MoMo's AI-first mission, we are designing and building a self-serve data platform to empower both internal teams and external partners. This platform allocates resources based on users’ needs to support:Ingesting data from diverse sources — either in batch or streaming, using both pull and push mechanismsDeveloping and deploying resilient data pipelines across the data lake, data warehouse, and streaming systemsDelivering high-quality, derived datasets to downstream tools such as BI solutions (e.g., Apache Superset, Google Data Studio), via multiple delivery methods including APIs, datasets, and streaming dataMonitoring data quality throughout all data pipelines in the platform to ensure high-quality data, resulting in better decision-making, accurate reporting, and reliable machine learning outputsTracking and optimising resource usage for efficiencyAdditionally, we are building Data Management Systems that enable the Data Governance team and data consumers to:Manage the full data lifecycle within the big data platformExplore the MoMo data ecosystem independentlyProvide a single source of truth with high data quality to downstream consumersTrack and manage infrastructure costs across major projects, teams, and departmentsYêu cầu công việcBachelor’s degree in Computer Science, Engineering, or a related fieldA problem solver with a strong sense of ownership and accountability — not just a task executor5+ years of experience working as a Data Engineer and 1+ year of experience working as leaderCurious and committed to lifelong learning, with a passion for solving business problems through engineering, improving service quality and usability, and maintaining a strong customer focusStrong foundation in computer science fundamentals, including data structures, algorithms, database systems, and data modelling techniquesProficient in at least one of the following languages: SQL, Python, JVM-based languagesExperience with databases such as PostgreSQL, MySQL, ClickHouse, DuckDB, etcSkilled in analysing, designing, implementing, and optimising Data Vault or Dimensional Modeling for performance and costHands-on experience with infrastructure platforms — cloud-based (e.g., GCP, AWS) or on-premise — and container orchestration using KubernetesExperience with data storage and processing engines like Apache Spark, Apache Flink, and StarRocksExperience with Google Cloud Platform or Amazon Web Services is a plus.

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.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sydney NSW, Australia; Melbourne VIC, Australia.Minimum qualifications: Bachelor's degree or equivalent practical experience. 10 years of experience with cloud native architecture in a customer-facing or support role. Experience in pre-sales or field engineering at an enterprise technology company, or similar customer facing experience. Experience engaging with, and presenting to, technical stakeholders and executive leaders. Experience in pre-sales management or people management on a data analytics-related or technical team. Experience with data analytics technologies or concepts, cloud, and on-premise technologies. Preferred qualifications: Experience influencing cross-functional teams (e.g., Product Management, Engineering, Sales), customers, and partners to impact business goals, customer experience, and customer expansion. Experience tailoring and delivering compelling messages to audiences, asking strategic questions, and leading conversations that drive business opportunity. Specialization in "Big Data," including analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, NoSQL, performance or scalability optimizations, or batch versus streaming. Thought leader in data analytics and adjacent practice areas, specialized in technical sales and strategizing around holistic customer and industry solutions. About the jobWhen leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products. Specialist Customer Engineers seek to accelerate Google Cloud customer success by providing domain-specific technical expertise, while responsibly influencing products and solutions.As a Customer Engineering (CE) Manager, you lead and deploy a team of subject matter experts responsible for working alongside our customers to provide trusted technical and solution advice to accelerate workload migration and remove technical impediments.Applicants must have a right to work in Australia as Google is currently unable to sponsor a visa for this position.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 a team of technical experts in a matrixed organization. Focus on talent strategy, assessing go-to-market readiness and gaps in CE preparedness, skills development, and opportunity coverage to deliver successful cloud transformation outcomes for customers and accelerate business goals. Execute the technical vision and strategy for your region’s data analytics practice. Lead the broader region's data analytics technical community, to ensure sub-regional technical contributions, achieve scale through artifact and innovation sharing. Influence cross-functional teams, including Product Management and Engineering, ensuring customer needs are represented in product roadmaps and new technology is incubated and scaled. Lead technical engagements with strategic customers, working with cross-functional peers to plan customer engagements. Travel up to 25% to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud. 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.

MoMo is the market leader in mobile payments in Vietnam. We strive to make all transactions fast, easy and joyful. We are looking for an experienced AI Engineer to join our growing Big Data AI team. At MoMo, we make AI/Machine Learning the core component to almost every part of the product - product recommendation, personalization, conversational AI, eKYC, risk scoring, fraud detection, promotion targeting and financial services. As a Senior AI Engineer, you will play a leading role in developing our Customer Service Chatbot system, delivering intelligent and seamless support experiences to millions of users.Mô tả công việcDesign, build, and optimize LLM-powered chatbot systems for customer service at scale;Develop and implement RAG (Retrieval-Augmented Generation) pipelines, prompt engineering strategies, and agentic workflows for domain-specific performance;Architect conversation flows, intent handling, and dialogue management systems that handle complex multi-turn interactions;Build evaluation frameworks and monitoring systems to measure chatbot quality, detect hallucinations, and ensure response accuracy;Collaborate cross-functionally with product, customer service operations, and engineering teams to continuously improve chatbot capabilities;Write production-grade code and maintain robust, scalable AI systems serving millions of users;Stay current with LLM advancements and evaluate new models, techniques, and tools for potential adoption.Yêu cầu công việc5+ years of experience as an AI Engineer, with at least 2 years focused on LLM applications or conversational AI systems;Deep understanding of LLM architectures, capabilities, and limitations (GPT, Claude, LLaMA, etc.);Experience building chatbot or virtual assistant systems, particularly for customer service use cases;Fintech domain experience is a strong plus;Proficiency in RAG systems, vector databases, embedding models, and prompt engineering techniques;Strong software engineering skills in Python. Experience with LLM tooling (LangChain, LlamaIndex, etc.);Experience with system design for high-availability, low-latency services;Familiarity with evaluation methods for generative AI systems and conversation quality metrics.

MoMo is the market leader in mobile payments in Vietnam. We strive to make all transactions fast, easy and joyful. We are looking for an experienced Software Engineer to join our growing Big Data AI team. At MoMo, we make AI/Machine Learning the core component to almost every part of the product - product recommendation, personalization, conversational AI, eKYC, risk scoring, fraud detection, promotion targeting and financial services.As a Software Engineer specializing in Natural Language Processing (NLP), you will play a pivotal role in crafting and deploying advanced conversational AI systems. This position offers a unique chance to make a significant impact by leveraging Generative AI and Large Language Models to transform interactions for millions of users. Join us in pushing the boundaries of AI technology and shaping the future of mobile payments in Vietnam.Mô tả công việcDevelop and Implement Conversational AI Solutions: Design, build, and maintain advanced conversational AI systems that enhance user interactions, utilizing cutting-edge NLP technologies and Generative AI.Contribute to System Architecture: Participate in the design and architecture of systems and infrastructure, ensuring robustness and scalability.Maintain High Standards of Code Quality: Write clean, maintainable, and efficient code in Kotlin and Python, and participate in code reviews to uphold the team's quality standards.Collaborate with Cross-Functional Teams: Work closely with product managers, data scientists, and other engineering teams to integrate AI-driven features into our platform, ensuring seamless user experiences.Yêu cầu công việcWhat we are looking forStrong Problem-Solving Skills: You have a proven track record of tackling complex technical challenges and delivering effective solutions, particularly in the realm of AI and machine learning.Ownership and Proactivity: You take initiative and are driven to see projects through from start to finish. You are someone who can be relied upon to deliver results with minimal supervision.Backend Engineering Proficiency: Minimum 5 years of experience as a Software Engineer, with strong skills in backend languages like Kotlin, Python, Java, or Go.High Standards for Quality: You take pride in your work and strive to deliver solutions that are not only functional but also maintainable and scalable.BenefitsCompetitive compensation package.Performance-based bonus.Insurance package.Chance to work with many strong people with international experience.