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Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Data Infrastructure designs, operates, and scales secure, privacy-respecting systems that power data-driven decisions across Anthropic. Our mission is to provide data processing, storage, and access that are trusted, fast, and easy to use. We're looking for infrastructure engineers who thrive working at the intersection of data systems, security, and scalability. You'll tackle diverse challenges ranging from building financial reporting pipelines to architecting access control systems to ensuring cloud storage reliability. This role offers the opportunity to work directly with data scientists, analysts, and business stakeholders while diving deep into cloud infrastructure primitives. Responsibilities: Within Data Infra, you may be matched to critical business areas including: Data Governance & Access Control: Design and implement robust access control systems ensuring only authorized users can access sensitive data. Build infrastructure for permission management, audit logging, and compliance requirements. Work on IAM policies, ACLs, and security controls that scale across thousands of users and systems. Financial Data Infrastructure: Build and maintain data pipelines and warehouses powering business-critical reporting. Ensure data integrity, accuracy, and availability for complex financial systems, including third party revenue ingestion pipelines; manage the external relationships as needed to drive upstream dependencies. Own the reliability of systems processing revenue, usage, and business metrics. Cloud Storage & Reliability: Architect disaster recovery, backup, and replication systems for petabyte-scale data. Ensure high availability and durability of data stored in cloud object storage (GCS, S3). Build systems that protect against data loss and enable rapid recovery. Data Platform & Tooling: Scale data processing infrastructure using technologies like BigQuery, BigTable, Airflow, dbt, and Spark. Optimize query performance, manage costs, and enable self-service analytics across the organization. You might be a good fit if you: Have 10+ years (not including internships or co-ops) of experience in a Software Engineer role, building data infrastructure, storage systems, or related distributed systems Have 3+ years (not including internships or co-ops) of experience leading large scale, complex projects or teams as an engineer or tech lead Can set technical direction for a team, not just execute within it Have deep experience with at least one of: Strong proficiency in programming languages like Python, Go, Java, or similar Experience with infrastructure-as-code (Terraform, Pulumi) and cloud platforms (GCP, AWS) Can navigate complex technical tradeoffs between performance, cost, security, and maintainability Have excellent collaboration skills - you work well with both technical and non-technical stakeholders Strong candidates may also have: Experience with security and compliance requirements (ITGC, GDPR, financial controls) Background in data warehousing, ETL/ELT pipelines, or analytics infrastructure Experience with Kubernetes, containerization, and cloud-native architectures Track record of improving data reliability, availability, or cost efficiency at scale Knowledge of column-oriented databases, OLAP systems, or big data processing frameworks Experience working in fintech, financial services, or highly regulated environments Security engineering background with focus on data protection and access controls Technologies We Use: Data: BigQuery, BigTable, Airflow, Cloud Composer, dbt, Spark, Segment, Fivetran Storage: GCS, S3 Infrastructure: Terraform, Kubernetes, GCP, AWS Languages: Python, Go, SQL Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Canada; Remote; Shanghai Workplace: remote ABOUT YOU   We are looking for a data-driven problem solver who thrives at the intersection of engineering and science. You have strong ownership and work autonomously in fast-paced environments, balancing velocity with reliability. As a collaborative mentor, you raise the bar for team quality and discipline while translating complex technical concepts into business value. You're passionate about building scalable solutions and have excellent cross-functional communication skills that bridge engineering and business stakeholders.   ABOUT US   Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. Responsibilities: 1. Architecture & Development Design, build, and optimize data pipelines and ETL workflows in Snowflake using Snowpark, Streams/Tasks, and Snowpipe. Develop scalable data models, Algorithm supporting user 360 views, churn prediction, and recommendation engine inputs. Lead integration across data sources: MySQL, BigQuery, Redis, Kafka, GCP Storage, and API Gateway. Implement CI/CD for data pipelines using Git, dbt, and automated testing. Define data quality checks and auditing pipelines for ingestion and transformation layers. 2. Leadership & Collaboration Mentor and guide junior data engineers on data modeling, performance tuning, and Snowflake best practices. Partner with Data Science, ML, and Backend teams to productionize machine learning features in Snowflake. Work closely with Legal, Security, and Infrastructure teams to ensure compliance, privacy, and governance of user data (PII). Collaborate with the Director of Data Platforms and product stakeholders to translate business requirements into technical specifications. 3. Performance & Scalability Tune algorithm performance. Establish data partitioning, clustering, and materialized views for fast query execution. Build dashboards and monitors for pipeline health, job success, and data latency metrics (e.g., via Looker, Tableau, or Snowsight). 4. Governance & Best Practices Establish and enforce naming conventions, data lineage, and metadata standards across schemas. Lead code reviews, enforce documentation standards, and manage schema versioning. Contribute to the company’s evolving data mesh and streaming architecture vision. Qualification & Skills: 5+ years of experience in Data Scientist, with 3+ years in Spark framework . Strong SQL and Python skills, with proven experience building ETL/ELT at scale. Deep understanding of algorithm performance tuning , query optimization , and warehouse orchestration . Experience with data pipeline orchestration (Airflow, Prefect, dbt, or similar). Solid understanding of data modeling (Kimball, Data Vault, or hybrid). Proficiency in Kafka , GCP , or AWS for real-time or batch ingestion. Familiarity with API-based data integration and microservice architectures . Preferred Experience lead machine learning teams or/and deploying ML feature pipelines . Background in ad-tech, gaming, or e-commerce recommendation systems. Familiarity with data contracts and feature stores (Feast, Tecton, or custom-built). Experience managing small data engineering teams and setting technical direction Strong ownership and ability to work autonomously in a fast-paced environment. Excellent cross-functional communication — can translate between engineering and business. Hands-on problem solver who balances velocity with reliability. Collaborative mentor who raises the bar for team quality and discipline Benefits: We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.   Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For the Data Scientist, we will conduct a background check that may include the following Criminal history check Employment verification Education verification   Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities Accessing confidential company data Ensuring compliance with regulatory requirements   Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com. By submitting the following job application form, you consent to Xsolla processing your data for career-related inquiries and potential employment opportunities. We process your data in accordance with this Xsolla Privacy Notice for Job Applicants. Please direct any inquiries regarding your data privacy to careers@xsolla.com.

Location: Ukraine We are looking to hire passionate Senior AI Engineers to help turn data into intelligent, production-ready solutions. You will work across the full AI stack: traditional machine-learning models, large language models (LLMs), computer-vision pipelines, and analytics / forecasting workflows. If you enjoy exploring data, building state-of-the-art models, and shipping reliable AI services, we would love to meet you. Responsibilities Model Development – Design, train, fine-tune, and evaluate models spanning classical ML, deep learning (CNNs, transformers), and generative AI (LLMs, diffusion). Data Exploration & Analytics – Conduct exploratory data analysis, statistical testing, and time-series / forecasting to inform features, prompts, and business KPIs. End-to-End Pipelines – Build reproducible workflows for data ingestion, feature engineering / prompt stores, training, CI/CD, and automated monitoring. LLM & Agentic AI Engineering – Craft prompts, retrieval-augmented generation (RAG) pipelines, and autonomous/assistive agents; fine-tune LLMs on domain-specific datasets to boost accuracy and align outputs with product requirements. AI Automation & Integration – Expose AI components as micro-services and event-driven workflows; integrate with orchestration tools (Airflow, Prefect) and business APIs to automate decision pipelines. Continuous Learning – Track advances in LLMs, vision, and analytics; share insights and best practices with the wider engineering team. Mentor junior engineers and contribute to technical direction and engineering best practices. Requirements BSc in Computer Science, Mathematics, or related field. 5+ years of professional experience working on AI/ML projects. Good command of English (written and spoken). Proficient in Python and core libraries (PyTorch / TensorFlow, scikit-learn, pandas, NumPy). Solid understanding of machine-learning algorithms, deep-learning fundamentals, and basic statistics. Experience with data wrangling and visualization (Matplotlib / Plotly) and exploratory analysis. Familiarity with at least one of: OpenCV, Hugging Face Transformers, LangChain, MLflow, or similar. Good grasp of software-engineering best practices: Git, code reviews, testing, CI. Preferred Qualifications Knowledge of C++ or C# for performance-critical modules. Experience deploying models via Docker, Kubernetes, or cloud AI services. Exposure to vector databases and RAG workflows. Skill in BI / dashboard tools (Power BI, Tableau, Streamlit) or time-series frameworks (Prophet, statsmodels). Familiarity with MLOps / LLMOps tooling (DVC, MLflow Tracking, Weights & Biases, BentoML). Experience with image processing techniques (e.g., OpenCV, image segmentation, feature extraction) Experience with Spark (PySpark) and distributed data processing, including usage of platforms such as Databricks, AWS EMR, or GCP Dataproc. Strong SQL skills and experience working with large-scale datasets, including partitioning and performance tuning. Familiarity with modern data lake architectures and scalable data storage concepts.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Claude App Infrastructure owns the reliability, experience, and agentic capabilities of claude.ai. We're the platform team for Anthropic's flagship consumer product, responsible for the serving architecture that keeps Claude available at scale, the conversation experience, and the infrastructure that lets every product team at Anthropic ship into claude.ai safely and fast. When the product grows at hyper scale, we're the team that makes sure it feels the same or better. Beyond the foundation, we're building the agentic layer that turns claude.ai from a chat surface into an execution surface: task execution, personalization, browser use, and server-side tools. This is where the next generation of the product gets built: the primitives that let Claude act in the world, not just respond. We believe reliability and velocity are the same problem, and our job is to build the systems that make both inevitable. Key responsibilities Design and build sandboxed compute environments where Claude can safely execute code, access tools, and interact with external services Build state management systems for long-running agent tasks, handling checkpoints, recovery, and resumption across failures Develop authentication and authorization frameworks for delegated access, so Claude can act on behalf of users securely Create observability and debugging tools for agent execution, so we understand what Claude did, why, and how to make it better Partner closely with product and research teams to define what's possible and ship it Minimum qualifications Experience building distributed systems, infrastructure, or platform services at scale Comfort building cloud native infrastructure on GCP, AWS, or Azure Experience with containers, sandboxing, or secure execution environments (e.g., gVisor, Firecracker, V8 isolates) Write clean, maintainable code in Python, Go, Rust, or a similar language Care about security, isolation, and building systems that fail safely Preferred qualifications Comfort with ambiguity and greenfield work where you help shape the architecture Interest in problems that don't have existing playbooks Experience building multi-tenant execution platforms or serverless infrastructure Background in security engineering, sandboxing, or isolation technologies Familiarity with workflow orchestration systems (Temporal, Airflow, Step Functions) Experience with state machines, checkpointing, or durable execution patterns Low-level systems experience (Linux internals, eBPF, container runtimes) The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote Poland, Poland Workplace: remote WELCOME TO OLX   We're building marketplace sustainable ecosystems that millions of people depend on every month – to buy and sell cars, find homes, land jobs, and trade secondhand goods. It's commerce that matters: safe, smart, and environmentally responsible.   We do this with courage to innovate, commitment to outcomes, collaboration across 50+ nationalities and 7 markets, and a customer-led approach that puts real people first. Add a desire to win – and you get a culture that's ambitious, fast-moving, and built on trust.   Our brands – including AutoTrader, OLX, Otomoto Property24, and more – are loved by millions. And we're backed by Prosus, one of the world's largest tech investors.   Join OLX and see how far you can go. ABOUT THE ROLE We are hiring a mid-level Data Engineer for our team.   Become a part of a team of data specialists who take care of massive amounts of data and groundbreaking technologies. Your work will be driving and empowering efficient and successful decentralised domain data ownership and data consumption, for example, around car pricing intelligence or deliveries. When needed, you can participate in the evolution and optimisation of our data stack, helping domains to ingest, process and consume data across the company. You will also play an active role in driving our agentic evolution roadmap. While being part of a central team of data engineers across Portugal, Poland and Spain, you will be embedded in cross-functional packs on a rotational basis. You will work closely with product managers, software engineers, product analysts, data scientists and regional business partners to identify and design new data projects and guide them through successful delivery and validation from end to end. What you will be doing: Enable efficient consumption of domain data as a product by delivering and promoting strategically designed actionable datasets and data models Build, maintain, and improve rock-solid data pipelines using a broad range of technologies Support teams without data engineers in building decentralised data solutions and product integrations. Build data pipelines in our Lakehouse using Medallion architecture. Act as a data ambassador, promoting the value of data and our data platform among engineering teams and enabling cooperation Cooperate with product teams to look for opportunities to integrate data into our end products and streamline source data so that data is cleaner earlier in the process Follow and promote data mesh principles around decentralised data ownership and ‘data as a product’ Promote and uphold privacy-by-design principles, ensuring sensitive data is managed in strict compliance with established security and privacy standards Increase data literacy of the engineering organisation by hosting training and mentoring other engineers (both less experienced data engineers and software engineers) Help advance agentic systems tailored for data engineering through the creation of specialized skills and agents. Who we are looking for: +2 years of experience building complex data pipelines and working with both technical and business stakeholders. Ability to think creatively; highly driven and self-motivated Master of SQL language regardless of the underlying data technology. Writes efficient, easy-to-read, and crisp SQL code. Familiarity with Medallion architecture. Experience with designing for scale and data growth in terms of storage and performance Business and product understanding (why over what) and the ability to deal with ambiguity Consistent track record of successful data projects delivered and managing their lifecycle Potential to build rock-solid Python applications - writes understandable and maintainable code Experience with cloud data technologies (AWS, GCP, or Azure Cloud), such as Redshift, Spark, Trino, Iceberg, Airflow. Knowledge and curiosity about other big data technologies and tools Experience with analytics teams and translating business terms and KPI to technical requirements Experience with defining and measuring data quality such as Monte Carlo or Great Expectations. Familiarity with Claude Code and/or Cursor, skills and AI agents Excellent written and verbal proficiency in English Based in Poland Our hiring process: Recruiter Interview Hiring Manager Interview Technical Interview Our benefits: Permanent contract (we are not offering a B2B option) Salary + annual bonus up to 15% of your annual gross salary IP Rights’ Costs (tax-deductible costs up to 70%) Work with and impact all OLX websites across Europe Train and conference budget A benefits package with 330 points on the Mybenefit platform per month, private medical care provided by Luxmed, Ask Henry services, and much more 100% remote work (and the possibility to work from our offices in Poznan and Warsaw) Diversity, Equity and Inclusion at OLX OLX values diversity and welcomes applicants of all races, ethnicities, disabilities, ages, genders, sexual orientations, religions, backgrounds, and experiences to apply. If this role excites you, we encourage you to apply, even if you don’t meet all the requirements - you may be just the right fit for this or other opportunities with us!   OLX will process your personal data to assess your fit for the applied position. You may optionally consent to store your data for up to 12 months after the application process for consideration in future OLX roles. For more details on how your application data will be processed please check our Privacy Statement.

Location: Pondicherry, India; Ahmedabad, India; Delhi, India; Bangalore, India Workplace: remote At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an Data Engineer to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Key Responsibilities: ● Design, develop, and maintain data ingestion pipelines using Kafka Connect and Debezium for real-time and batch data integration. ● Ingest data from MySQL and PostgreSQL databases into AWS S3, Google Cloud Storage (GCS), and BigQuery. ● Implement best practices for data modeling, schema evolution, and efficient partitioning in the Bronze Layer. ● Ensure reliability, scalability, and monitoring of Kafka Connect clusters and connectors. ● Collaborate with cross-functional teams to understand source systems and downstream data requirements. ● Optimize data ingestion processes for performance and cost efficiency. ● Contribute to automation and deployment scripts using Python and cloud-native tools. ● Stay updated with emerging data lake technologies such as Apache Hudi or Apache Iceberg. Required Skills and Qualifications: ● 5+ years of hands-on experience as a Data Engineer or similar role. ● Strong experience with Apache Kafka and Kafka Connect (sink and source connectors). ● Experience with Debezium for change data capture (CDC) from RDBMS. ● Proficiency in working with MySQL and PostgreSQL. ● Hands-on experience with AWS S3, GCP BigQuery, and GCS. ● Proficiency in Python for automation, data handling, and scripting. ● Understanding of data lake architectures and ingestion patterns. ● Solid understanding of ETL/ELT pipelines, data quality, and observability practices. Good to Have: ● Experience with containerization (Docker, Kubernetes). ● Familiarity with workflow orchestration tools (Airflow, Dagster, etc.). ● Exposure to infrastructure-as-code tools (Terraform, CloudFormation). ● Familiarity with data versioning and table

Location: Germany; Israel; Netherlands; Prague, Czech Republic; Remote - Europe; United Kingdom About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role The Data Engineering team builds and operates the data platform that powers analytics, business intelligence, operational reporting, and data-driven products across Nebius. We ingest data from internal and external systems, develop reliable transformation pipelines and data models, and make trusted datasets available to business and product teams. We are looking for a Senior Data Engineer to own substantial parts of our data platform and deliver complex data products end to end. You will turn ambiguous business needs into pragmatic technical solutions, make architecture and implementation trade-offs, and improve the reliability, scalability, and usability of our data ecosystem. You will work closely with product, platform, and business teams, helping them use data effectively while ensuring that our systems remain maintainable and trustworthy as Nebius grows. Your responsibilities : Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business and analytical requirements into scalable data models, reliable data products, and clear technical plans. Design and evolve data architecture, storage, processing, and orchestration patterns for large-scale workloads. Improve data quality, observability, lineage, and incident response for critical datasets and pipelines. Investigate and resolve challenging performance, reliability, and data-correctness issues in production. Establish reusable tools, conventions, and automation that improve engineering productivity and reduce operational risk. Work with product teams and business stakeholders to define data contracts, priorities, and success criteria. Contribute to technical direction through design reviews, thoughtful trade-offs, and documentation. Support and mentor other engineers through reviews, pairing, and knowledge sharing. Participate in the on-call rotation and take ownership of improving the operational health of the systems you support. Must-haves : 5+ years of experience in data engineering, backend engineering, or a related role; or equivalent experience delivering and operating production data systems. Proven experience independently delivering complex data pipelines or data-platform capabilities from problem definition through production operation. Strong Python and SQL skills, including writing maintainable production code and optimizing non-trivial queries. Hands-on experience with workflow orchestration tools such as Airflow, Prefect, or Dagster. Strong understanding of data modeling, including designing maintainable analytical models and data contracts for multiple consumers. Solid knowledge of data architectures and storage systems, including the trade-offs between different processing and storage approaches. Experience designing for reliability: testing, monitoring, data-quality validation, alerting, debugging, and incident resolution. Ability to make technical decisions under ambiguity, explain trade-offs clearly, and collaborate effectively with engineers and non-technical stakeholder Nice - to - have s : Experience with real-time or event-driven data platforms and streaming technologies. Experience building or operating cloud-native services with Docker and Kubernetes. Familiarity with Infrastructure as Code, particularly Terraform. Experience with data governance, access control, privacy, and compliance requirements such as GDPR or SOC 2. Experience with data observability and quality tools or frameworks, such as Great Expectations. Experience improving engineering standards through shared libraries, platform tooling, technical documentation, or mentoring. We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Mapbox Germany Workplace: Remote Mapbox is the leading real-time location platform for a new generation of location-aware businesses. Mapbox is the only platform that equips organizations with the full set of tools to power the navigation of people, packages, and vehicles everywhere. More than 4 million registered developers have chosen Mapbox because of the platform’s flexibility, security and privacy compliance. Organizations use Mapbox applications, data, SDKs and APIs to create customized and immersive experiences that delight their customers.  WHAT WE DO The Navigation team https://www.mapbox.com/navigation at Mapbox develops and operates web services powering virtually all of Mapbox’s strategic navigation initiatives in consumer, automotive, and logistics verticals. We are a highly multidisciplinary organization, with work spanning distributed systems on AWS to geospatial localization, traffic telemetry, and mapping. Collectively we are revolutionizing in-car experiences with technology to build fast, industry-leading maps and navigation for any vehicle. We’ve launched products such as MapGPT https://www.mapbox.com/mapgpt, Mapbox for EV https://www.mapbox.com/ev, and we’re enhancing the visual experience of in-vehicle navigation with 3D styling with our new Mapbox Standard through web and mobile SDKs. Mapbox has worked with automotive partners https://www.mapbox.com/automotive— including BMW, Toyota, and GM — to bring the best aspects of mobile app development into in-vehicle navigation and infotainment. - Mapbox Blog: Introducing 3D Live Navigation https://www.mapbox.com/blog/mapbox-3d-navigation - Mapbox Blog: Route Notifications Improve Driver Safety https://www.mapbox.com/blog/route-notifications-improve-driver-safety - Mapbox Newsroom: AI Features in New Navigation SDK https://www.mapbox.com/press-releases/mapbox-unveils-ai-features-in-new-navigation-sdk As AI becomes embedded in modern engineering workflows, we value engineers who can thoughtfully integrate AI into design, development, and decision-making. Our interview process will include discussion of how you use AI in your engineering workflow. WHAT YOU’LL DO As a Machine Learning Engineer III on the Routing Cost team, you will lead the design, development, and delivery of highly trafficked recommendation systems for our routing cost engine. Your technical contributions will include: - Lead the engineering team(s) to execute end-to-end feature implementation within the larger navigation organization (~80 engineers). - Design and build new ML and data pipelines, as well as optimizing existing ML and data pipelines. - Build tools for automated quality assurance and data exploration. - Leverage geospatial algorithms to optimize pipelines, as well as creating automated tuning and outlier detection algorithms. - Partner with data scientists to make improvements to our models for determining patterns in movement and/or traffic. - Mentor colleagues and participate in code and design reviews. - Participate in an on-call rotation to ensure our systems remain available to customers 24/7. Team members alternate as the on-call primary responder, which may require immediate response outside normal working hours, including weekends. WHAT WE BELIEVE ARE IMPORTANT TRAITS FOR THIS ROLE - 8-10+ years of backend and ML experience: Extensive hands-on experience showcasing expertise and a strong track record in the engineering field. Experience with Reinforcement Learning. - Technical knowledge: Extensive experience with Python, distributed processing pipelines (Hadoop, Spark, Airflow, Dask), and very large datasets – statistical analysis, data quality control, optimizing storage. - Cloud proficiency: Extensive experience with cloud and infrastructure services, including, as well as deploying and managing infrastructure in cloud environments. - Operational excellence: You drive a culture of quality and continuous improvement in your organization. Strong passion for clean code and robust architecture, with a drive to elevate engineering practices and design standards across the team. - Ownership & execution: Own the technical vision, lead the strategy and guide the team to execute towards building the future of our routing cost engine. - Customer focus: You care deeply about your customers and their problems, and you work tirelessly to innovate on their behalf. - Growth mindset: Have the humility to accept mistakes, learn and grow from them. - Mentorship: Experience mentoring and leading engineering teams developing skill sets and career growth. - Strong written and vocal communication skills: You can talk and write about complex ideas concisely to a wide audience. You are able to lead and resolve org-wide technical discussions and are able to collaborate and include input from cross-functional teams (security, devops, data, compliance and product). - Data informed mindset: You believe in the value of data informed decision making and strive to measure things that are not straight forward but essential. You also have the right instincts to make speedy decisions in the absence of perfect & comprehensive data. EMPLOYMENT REQUIREMENTS - Employment Type: Full-time - Weekly Hours: 40 hr per week - Location/Hybrid Policy: Remote (from any city in Germany) WHAT WE VALUE In addition to our core values https://www.mapbox.com/about/values/, which are not unique to this position and are necessary for Mapbox leaders: - We value high-performing creative individuals who dig into problems and opportunities. - We believe in individuals being their whole selves at work. We commit to this through supportive health care, parental leave, flexibility for the things that come up in life, and innovating on how we think about supporting our people. - We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company. - We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply. HOW WE SUPPORT YOU - Hybrid/Remote Options: Enjoy flexibility to work comfortably from home or periodically from an office where applicable. - Country-Specific Care & Coverage: Private health, dental, and income protection plans tailored to elevate your regional statutory benefits. - Family-First Support: Family care, maternity and paternity leave policies to support your growing family. - Lifestyle Spending Account: Contributions to support your health, wellness, and personal growth - Balance & Brainpower: Mental health support for you and your dependents. - Rest & Recharge: Paid time away, company holidays, and generous absence policies. - Time Off to Give Back: Dedicated paid volunteering time in addition to your standard PTO. By applying for this position, you acknowledge that you have received the Mapbox Non-US Privacy Notice https://www.mapbox.com/legal/applicant-privacy-notice/ for applicants, which is linked here.  Completing this application requires you to provide personal data, such as your name and contact information, which is mandatory for Mapbox to process your application.  We are committed to a fair and equitable hiring process. We do not discriminate against any protected class. #LI-Remote

Location: Islamabad, Pakistan; Punjab, Pakistan; Karachi, Pakistan Workplace: remote At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an Data Architect to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Role Summary: The Data Architect will design and govern the complete data ecosystem for the ValueX platform — including data ingestion, processing, modeling, storage, orchestration, and governance. They will define the data architecture blueprint supporting the system’s core modules. 1. Customer Segmentation 2. Business Decisioning & Offer Assignment Engine 3. Real-Time Offer Orchestration Module (ROOM) 4. ML/AI Model Management & Simulation Engine The architect will ensure scalability to handle 50 million+ customer profiles, real-time event streams, and ML-driven decisioning — with a focus on performance, cost optimization, and maintainability. Key Responsibilities: Data Architecture & Design Define the end-to-end data architecture across batch, streaming, and real-time layers. Design Customer 360 and Offer 360 data models, including feature store and historical layers. Establish logical, physical, and semantic data models to enable segmentation, scoring, and orchestration. Define data contracts for Kafka topics, API payloads, and Adobe/CDP integrations. Set up data versioning and lineage frameworks to track data provenance Data Ingestion & Integration Architect data ingestion pipelines from multiple telco sources: OCS, CRM, Kenan, Billing, DWH, Adobe AEP, Pricefx, and external APIs. Define patterns for real-time event ingestion (recharge, offer purchase, balance check). Standardize data access through APIs or data products for downstream modules. Design connectors for cloud storage (e.g., S3, Delta Lake) and integration middleware (e.g., n8n, DecisionRules.io , KNIME). Data Management & Governance Define and enforce data quality, lineage, catalog, and access policies. Establish metadata management frameworks (e.g., DataHub, Collibra, Amundsen). Set up data validation and DQ frameworks (Great Expectations, Deequ). Govern data partitioning, schema evolution, retention, and archiving strategies. Ensure compliance with data privacy and regulatory standards (e.g., PDPA, GDPR, local telecom data policies). Scalability, Cost & Performance Design for high performance and cost-efficient scalability (25M → 50M → 75M customers). Optimize compute/storage balance across environments (Dev, UAT, Prod). Define data lakehouse optimization strategies (Z-Order, Delta caching, compaction). Monitor and manage query performance, cluster sizing, and job orchestration costs. Collaboration & Governance Work closely with Data Engineers, Data Scientists, and Application Developers to ensure architectural alignment. Lead architecture review boards and maintain data design documentation (ERD, flow diagrams, schema registry). Serve as technical liaison between business stakeholders, data teams, and platform vendors (Databricks, Adobe, Pricefx). Provide best practices and design patterns for model deployment, retraining, and data lifecycle management. 10+ years in Data Architecture and Data Platform Design Data Architecture-Data lakehouse design, data modeling (dimensional, normalized, semantic), schema management. ETL/ELT & Orchestration-Databricks, Snowflake, dbt, Airflow, AWS Glue, Azure Data Factory. Streaming & Real-Time-Apache Kafka, Spark Streaming, Kinesis, Flink Data Modeling-Customer 360, Offer 360, Transaction 360, Feature Store Cloud Platforms-AWS (S3, Glue, Lambda, EMR), Azure (ADF, Synapse), or GCP (BigQuery, Dataflow) Storage & Compute-Delta Lake, Parquet, Iceberg, Snowflake Data Quality & Governance-Great Expectations, Deequ, DataHub, Collibra Programming & Scripting-Python, SQL, PySpark, YAML API & Integration Design-REST, GraphQL, Kafka Connect, JSON schema Security & Compliance-IAM, encryption (KMS), access control, masking, PDPA compliance Preferred (Nice-to-Have) Telecom industry experience (recharge, balance, offer, churn, usage data). Experience integrating with Adobe Experience Platform (AEP) or Pricefx. Knowledge of DecisionRules.io , KNIME, or n8n for workflow orchestration. Familiarity with AI/ML pipelines and MLOps frameworks (MLflow, SageMaker). Exposure to knowledge graphs (Neo4j, GraphFrames) for segmentation and recommendation. Educational Background Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related fields. Certifications in AWS/Azure Data Architect, Databricks Certified Data Engineer, or Snowflake Architect are preferred.

Location: Doha Workplace: OnSite ABOUT THE STUDIO Utopia Studio is an AI-native venture builder for the Global South, backed by Qatar Development Bank. We work with domain experts across the GCC, Southeast Asia, and Africa to accelerate venture creation through AI-driven execution and shared infrastructure. At the core is Utopia OS — a modular platform that automates what's repeatable, embeds AI agents across workflows, and lets learning compound across ventures. ABOUT THE ROLE We're looking for a founding product engineer to build the platform and infrastructure side of Utopia OS. You’ll design, develop, and scale the shared systems, data pipelines, and full-stack applications that power dozens of AI-native ventures launching from Doha for the Global South. You’ll combine deep backend expertise with the ability to deliver seamless, data-driven web experiences that make AI-native venture building faster and smarter. You will work as part of a product trio with the Design Lead and the Rapid Prototyping Engineer, making joint decisions on discovery, scope, and technical approach. Reports to: Studio Director Growth path: Head of AI Platform / CTO track RESPONSIBILITIES PLATFORM ENGINEERING & INFRASTRUCTURE - Architect, build, and maintain Utopia OS infrastructure: auth, data systems, deployment, monitoring, analytics - Develop full-stack web apps and plugins for studio-wide decisioning and analytics - Build and maintain data pipelines for ingestion, transformation, and deployment across all ventures - Develop and maintain robust backend systems and APIs, integrating modern databases (Postgres, Supabase, PlanetScale) and data architectures (Iceberg, Delta Lake). - Implement data pipelines and transformation workflows (Dagster, Airflow) to enable real-time analytics across ventures. - Create clear, reusable documentation and internal tooling to standardize engineering practices across the platform. - Take early-stage products and harden them for scale, reliability, and compliance. - Collaborate with design and product teams to translate data and infrastructure capabilities into intuitive user experiences and venture-facing tools. - Implement CI/CD, observability, and security frameworks across the portfolio - Design deployment templates for multi-tenant environments and enterprise integrations COLLABORATION & ENGINEERING EXCELLENCE - Work closely with venture teams to integrate AI workflows and shared infrastructure - Improve developer experience through modern, intuitive tool design - Provide technical guidance and mentorship to engineers and fellows — fostering a culture of learning, experimentation, and shared standards across the Studio. - Document architecture, standards, and playbooks so they can be reused across the studio - Communicate complex technical concepts clearly to both engineering and non-technical stakeholders — turning systems thinking into shared understanding. - Stay current with advances in generative AI, data infrastructure, and modern web engineering - Work in a tight loop with the Design Lead on design system needs and with the Rapid Prototyping Engineer to productionize validated prototypes into secure, scalable services. - Co-own technical discovery with the product trio: define evaluation plans, success metrics, and risks before committing to builds. - You’ll also help the team build shared capabilities typically owned by dedicated functions — like LLMOps, Data Engineering, and Security — but in a lean, integrated way. - That means establishing lightweight evaluation pipelines, data ingestion templates, and security practices that can scale across multiple ventures without extra overhead. - These foundations will later evolve into formalized systems as Utopia grows. - We operate as a compact, AI-native core team — covering product, design, and engineering end-to-end. - Each of us contributes to early foundations in areas like evaluation, data, research, and security, ensuring the platform scales responsibly without added layers or headcount. EXPERIENCE & SKILLS - Bachelor's or Master's in Computer Science, Software Engineering, or related field - 4–8 years in full-stack and backend development (startup or AI context preferred) - Strong with modern frameworks (React, Vue, Angular, Next.js, SvelteKit) and backend systems (Postgres, Supabase, PlanetScale) - Experience with data pipelines (Dagster, Airflow) and modern data lakes (Iceberg, Delta Lake) - Experience designing data-driven applications — integrating analytics and visualization into user-facing tools. - Comfortable with cloud platforms (AWS/GCP/Azure), Docker, Kubernetes, and CI/CD pipelines - Strong documentation and communication skills — you can explain complex systems clearly TECHNICAL FOUNDATIONS - Strong in full-stack development, with expertise in at least one modern front-end framework (React, Svelte, Vue, Angular, or Next.js) - Experienced with backend systems, data pipelines, and cloud infrastructure (Postgres, Supabase, AWS, Docker, Kubernetes) - Comfortable developing and deploying in hybrid environments, with CI/CD, monitoring, and observability best practices - Familiar with data lake architectures (Delta Lake, Iceberg) and workflow orchestration tools (Airflow, Dagster) IMPACT & SUCCESS METRICS - Accelerate venture build cycles through reusable systems and faster deployment - Improve infrastructure reliability and security across ventures - Reduce duplication and increase code reuse across the Studio platform - Enable measurable improvements in venture launch speed, uptime, and developer experience MINDSET & VALUES - Systems + Empathy: You balance deep backend expertise with product intuition and user empathy. - AI as collaborator: You build infrastructure that learns, adapts, and improves through automation and AI augmentation. - Outcome focus: You optimize for speed, reliability, and measurable business value across all ventures. - Continuous learning: You're always exploring new frameworks, architectures, and AI tools that make engineering smarter and more efficient. WHAT YOU CAN EXPECT - Meaningful Impact: Your work directly contributes to building the core infrastructure behind a new generation of ventures - enabling equitable, AI-native innovation across the Global South. - Collaborative Culture: We thrive on openness, curiosity, and collective intelligence. Everyone has a voice, and decisions are made transparently. - Growth Mindset: From AI learning and use budgets to mentorship, we invest in your development and help you grow beyond your comfort zone. - Competitive Rewards: Tax-free compensation, private health and travel insurance, and a benefits package designed for both security and flexibility. - Wellbeing First: Generous PTO, flexible hybrid setup, and wellness programs to help you stay balanced. - Work-Life Integration: Office lunches twice a week, great snacks, and team meetups that keep energy and connection high. - Global Exposure: Occasional travel across Southeast Asia, Africa, and the Middle East for meaningful, on-ground collaboration with venture teams. - Inclusive by Design: We celebrate diversity and are committed to building an environment where everyone belongs. WHY THIS ROLE MATTERS You'll be building the operating system for AI-native venture creation — the foundation that founders across the Global South will use to build the next generation of companies. Your work will power Utopia OS and enable innovation aligned with Qatar's Vision 2030 for a digital, knowledge-based economy. Your work will accelerate venture build time and reduce technical duplication across the Studio — measurable through faster deployment cycles, improved reliability, and reusable systems. WHO THIS ROLE ISN’T RIGHT FOR If you prefer working in rigid environments, or need fully defined specs before shipping, this may not be the right fit. We move fast, operate with high trust, and expect engineers to take ownership from architecture through to production. THE UTOPIA PLATFORM ADVANTAGE The Studio is part of Utopia Capital’s integrated venture platform designed to solve the biggest friction points in emerging market venture creation. Most founders face a broken journey: they struggle to build with limited resources, chase capital across disconnected investors, and lack the infrastructure to scale across regions. We've built a different system. The Studio co-builds ventures with domain experts using AI-native infrastructure, compressing the path from concept to product. The Radical Fund and A-typical Ventures provide fast, aligned capital from pre-seed through Series A, removing fundraising friction at every stage. And Utopia OS — our shared technical backbone — gives every venture access to the same tools, data systems, and regional networks that would normally take years and millions to build. This means founders can focus on solving real problems while we handle the build infrastructure, capital coordination, and cross-regional expansion. It's a compounding system: each venture we build makes the next one faster, smarter, and more capital-efficient. That's the platform advantage that you will be part of and contribute to, purpose-built for the complexity of the Global South. We believe innovation should be inclusive and globally distributed. Our team is built on openness, curiosity, and collaboration — with people from across the GCC, Africa, and Southeast Asia working together to build meaningful ventures. All roles are based in Doha, Qatar, with flexible hybrid options and global travel opportunities (unless otherwise stated). We welcome talent from every background to join us in shaping the future of AI-native innovation.

Location: New York, NY (HQ); San Francisco, CA Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE Growth engineering builds the systems and applications that power every growth channel at Ramp. As an engineer on this team, you’ll own foundational problems ranging from high volume data ingestion and interfaces to customer-facing applications and AI-powered workflows. You’ll partner closely with product, data, and design, and work directly with stakeholders across growth, sales, and finance. This role offers high ownership, broad technical scope, and the opportunity to directly shape Ramp’s growth engine and scale Ramp to its next millions of users. Check out our Engineering Blog https://builders.ramp.com/ to learn more about our tech stack, mission, and values! WHAT YOU’LL DO - Build software that helps grow Ramp to its next millions of users - Build and scale internal platforms and applications (e.g. workflow orchestration, incentives, sales and marketing apps) that power growth across the company - Design and maintain data ingestion and activation pipelines across Ramp products, internal business systems, external systems, and third-party data - Apply AI/LLMs to unstructured data processing, automation, personalization, and growth signal derivation - Drive business outcomes through experiments and metric-driven software development - Make thoughtful prioritization and scoping decisions around when to build custom solutions vs. leverage third-party tools - Work in a fast-moving, collaborative engineering team alongside partners in product, data, and design WHAT YOU NEED - Minimum of 3 years of experience in a software development role - Experience shipping fast, reliable applications using modern development tools and infrastructure - Comfort operating in a fast-paced, constantly evolving startup environment - Ability to improvise and develop creative solutions when standard approaches fall short; strong bias toward pragmatism in the face of uncertainty - Perpetual curiosity and a passion for continuously improving your craft NICE-TO-HAVES - Startup experience as a technical co-founder or early engineer - Experience with the modern data stack (e.g. ETL tools like Fivetran, workflow orchestrators like Airflow, data platforms like Snowflake) - Experience applying AI/LLMs in production environments - Strong perspective on the engineering development lifecycle (system design, documentation, testing, and long-term codebase health) - Experience building user-facing data or internal business applications - Familiarity with tools that power marketing and sales automation, personalization, and analytics BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: San Francisco; New York Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE As a Software Engineer on the Training Infrastructure team, you'll architect and lead development of our training platform, supporting top tier research engineers and model developers. You'll make key technical decisions for the infrastructure enabling developers to deploy, scale, and monitor their workloads with high performance and reliability. You’ll own scheduling, storage, networking, reliability, and observability of technical systems in the training stack EXAMPLE INITIATIVES Take a look at what we’ve built so far: - Overview of the product so far https://www.baseten.co/blog/baseten-training-is-ga/#training-is-now-ga - Training docs overview https://docs.baseten.co/training/overview - Story of the Training product https://www.baseten.co/blog/a-q-a-from-inference-to-training-the-inside-story-of-baseten-s-newest-product/ - Research we've done https://www.baseten.co/resources/research/ RESPONSIBILITIES - Design and architect scalable infrastructure systems for our ML training platform (e.g. scheduling, storage, and networking) - Partner closely with developers and research engineers to translate complex training requirements into technical solutions - Design and architect a global training scheduler - Design and architect reinforcement learning systems and continuous learning pipelines - Drive long-term improvements to increase reliability of systems and velocity of development - Partner closely with SRE and Capacity teams to unlock state of the art training infrastructure - Make critical architectural decisions balancing performance with system reliability - Lead technical discussions and mentor junior engineers on infrastructure best practices - Contribute to long-term technical strategy and infrastructure roadmap REQUIREMENTS - Bachelor’s degree or higher in Computer Science or related field - 5+ years of experience - Proficiency in Go, with - Deep expertise with Kubernetes in production environments - Advanced understanding of distributed systems concepts and performance tuning - Proven experience designing observability systems - Experience with ML/AI workloads and MLOps platforms NICE TO HAVE - Experience with distributed storage systems - Python experience a plus - Extensive experience with major cloud providers (AWS, GCP) and neo-cloud providers (Crusoe, DigitalOcean, Nebius) - Experience with workload orchestration platforms like Temporal or Airflow - Familiarity or experience with the open source training stack and frameworks (NCCL, PyTorch, Megatron, NemoRL, VeRL, Axolotl, HF Trainer) and distributed training techniques (FSDP, DeepSpeed). - Experience developing AI products, tooling, or agents BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Paris Workplace: Hybrid ABOUT VOODOO Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz. TEAM The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile gaming industry. Within the Data team, you’ll join the BI/Prediction Team which is an autonomous squad of around 10 people. The team is composed of top-tier product managers, software & data engineers, data scientists and data analysts. ROLE The objective of this team is to accelerate the growth of the company by serving as the on-demand prediction provider for all Voodoo BUs. This involves addressing critical needs such as predicting campaign LTV for User Acquisition optimization, determining optimal monetization offers for millions of players or constructing confidence intervals for time series data prediction. We want to onboard a passionate senior data scientist with significant experience in a similar environment to allow us to go one step further. This is an opportunity to have a strategic and critical impact on Voodoo’s success. This position is hybrid and requires 3 days per week in the office based in Paris. - Take ownership of our products modeling pipelines - Contribute to high modeling performance through insightful ideas and initiatives. - Build and deploy quickly scalable ML systems. - Engage with colleagues across the company to leverage new ideas and perspectives and demonstrate excellent communication to efficiently cooperate with product managers, teammates and stakeholders. - Deep dive into data to discover relevant insights. - Build a rich understanding of the mobile gaming industry, the company strategy, our products and their fit within the company’s daily operations. - Mentor and guide a team of data scientists, fostering technical excellence and autonomy. - Establish and enforce best practices in ML engineering, experimentation, and reproducibility across projects. - Champion a culture of impact-driven research, ensuring models not only perform well technically but also create tangible business value. - Proactively identify risks in modeling approaches, data quality, scalability, business alignment and design mitigation strategies. PROFILE - Extensive experience building machine learning systems - Extensive experience with Python, SQL and MLOps best practices - Cloud experience needed (ideally AWS but could be another cloud provider) - Airflow and DBT experience is a nice to have - Excellent Communication in English and French mandatory - You enjoy working in a team, learning new things, sharing knowledge - Experience in a tech startup/scaleup is a plus - Strong achievements on Kaggle will be valued BENEFITS - Competitive salary - Comprehensive relocation package (including visa support) - Premium healthcare (SideCare) for you and your family 100% borne by Voodoo - Swile Lunch voucher - Gymlib (100% borne by Voodoo) - Wellness activities in our Paris office - Unlimited vacation policy - Remote days - Child daycare facilities (Les Petits Chaperons rouges)

Location: Limassol, Cyprus We are looking for a Data Governance Analyst to join our team.RequirementsBusiness Metrics & Data Governance: experience documenting and standardizing business metrics, KPIs, business glossary, and business logic to establish a single source of truth across the organization.Data Quality: hands-on experience translating business requirements into measurable Data Quality rules and implementing automated validation using Great Expectations, Soda, dbt Tests, or similar frameworks.SQL & Python: strong SQL and Python skills for data validation, automation, framework development, and root cause analysis of data quality issues.Metadata Management: experience with data catalog and metadata management platforms (OpenMetadata, DataHub, or similar) to maintain metadata, lineage, and documentation.Data Governance Principles: solid understanding of Data Governance, Data Stewardship, Data Lineage, Metadata Management, and Data Lifecycle Management to support scalable governance practices.AI: practical experience using AI tools to automate workflows, improve productivity, and enhance data analysis and documentation processes.Nice to haveExperience with streaming technologies (Kafka, Spark, Flink).Experience with orchestration tools (Airflow, Dagster) and CI/CD.Experience with semantic/metrics layer tools (dbt Semantic Layer, Cube, LookML).Knowledge of data privacy and security standards (GDPR, CCPA).Previous experience in iGaming or FinTech.ResponsibilitiesDefine and standardize business metrics, KPIs, and business glossary together with stakeholders to ensure consistent business definitions across the company.Drive Data Governance adoption by introducing standards, best practices, and governance processes across data domains.Design and develop the company's Data Quality framework, including validation rules, monitoring, and quality standards to improve data reliability.Implement and maintain automated Data Quality checks and anomaly detection to proactively identify and resolve data issues.Build and manage the data catalog, metadata, and data lineage to improve data discoverability and transparency.Collaborate with Data Engineers to integrate Data Quality controls into data pipelines and investigate data inconsistencies across systems.We offer:High salary (plus performance bonuses and salary revision);Work schedule: Mon-Fri (9h with 1h lunch break), flexible start 8:00-10:00;24-days holiday leave;First line seaview from your office;Corporate English and Greek lessons;GYM and SPA in the office;Corporate meals;Eventful corporate life;Exciting work challenges that allow you to grow to your full potential;Strong team of like minded professionals who will be by your side to accomplish ambitious projects, and to stimulate your professional development and bring experience.

Location: London DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk. Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets. We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus. About the Team The DRW C/FICCO Data Engineering team is essential to developing valuable datasets and scalable data infrastructure critical to our trading operations. We work closely with traders, researchers, and other engineering teams to ensure seamless data flow and accessibility, supporting data-driven decision-making. Our systems are designed to handle large volumes of data, maintain quality and integrity, and provide robust APIs for fast, ergonomic data retrieval. About the Role In this role you will: Collaborate with cross-functional teams to deliver data solutions that support diverse trading activities. Take full ownership of data products, guiding them from initial concept through to stable production. Design, build, and maintain systems for both batch processing and real-time streaming of time series datasets, ensuring high data quality and reliability. Develop APIs and data access methods for fast, intuitive retrieval of historical and live data, working with both new and existing systems. Provide on-call support as needed. Qualifications: A minimum of 2+ years’ experience using at least one of Python, Java, and C++, and can work comfortably in multiple programming languages A track record of working directly with end customers, scoping and delivering production systems in fast-moving and ambiguous environments Ability to dive deep into complex problems, develop intuitive understandings, spot risks early, and minimize complexity Exceptional interpersonal skills - you communicate clearly with stakeholders as well as other engineers, fostering a collaborative, supportive working environment Experience in the financial markets, especially in delta one, store of value, and/or FICC options trading Experience with Linux-based, concurrent, high-throughput, low-latency software systems Experience with pipeline orchestration frameworks (e.g. Airflow, Dagster) Experience with streaming platforms (e.g. Kafka), data lake platforms (e.g. Delta Lake, Apache Iceberg), and relational databases Have a Bachelors or advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or equivalent work experience For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice . California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice . #LI-BL1

Location: Remote - United States Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. What You’ll Do Design, build, and deploy production-grade machine learning models and systems at scale Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring Build scalable data and model pipelines with strong reliability, observability, and automated retraining Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions Improve system performance across latency, throughput, and model quality metrics Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment Contribute to technical strategy, architecture, and long-term ML roadmap Basic Qualifications 3-5+ years of experience building, deploying, and operating machine learning systems in production Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs) Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow) Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions Experience improving measurable metrics through applied machine learning Preferred Qualifications Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.) Experience working with real-time systems and low-latency production environments Background in feature engineering, model optimization, and production monitoring Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale Advanced degree in Computer Science, Machine Learning, or related quantitative field Potential Teams Ads Measurement Modeling Ads Targeting and Retrieval Advertiser Optimization Ads Marketplace Quality Ads Creative Effectiveness Ads Foundational Representations Ads Content Understanding Ads Ranking Feed Relevance Search and Answers Relevance ML Understanding Notifications Relevance Benefits Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/ . To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $216,700 — $303,400 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: Remote - Ontario, Canada Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. What You’ll Do Design, build, and deploy production-grade machine learning models and systems at scale Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring Build scalable data and model pipelines with strong reliability, observability, and automated retraining Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions Improve system performance across latency, throughput, and model quality metrics Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment Contribute to technical strategy, architecture, and long-term ML roadmap Basic Qualifications 3-5+ years of experience building, deploying, and operating machine learning systems in production Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs) Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow) Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions Experience improving measurable metrics through applied machine learning Preferred Qualifications Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.) Experience working with real-time systems and low-latency production environments Background in feature engineering, model optimization, and production monitoring Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale Advanced degree in Computer Science, Machine Learning, or related quantitative field Potential Teams Ads Measurement Modeling Ads Targeting and Retrieval Advertiser Optimization Ads Marketplace Quality Ads Creative Effectiveness Ads Foundational Representations Ads Content Understanding Ads Ranking Feed Relevance Search and Answers Relevance ML Understanding Notifications Relevance Benefits Comprehensive Healthcare Benefits and Income Replacement Programs 401k with Employer Match Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support Family Planning Support Gender-Affirming Care Mental Health & Coaching Benefits Flexible Vacation & Paid Volunteer Time Off Generous Paid Parental Leave In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable.  We will not sell your personal information or disclose it to any third party for their marketing purposes.  We will delete any recording of your interview promptly after making a hiring decision.  For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors . Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve.  Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

Location: Singapore, Singapore OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa. Who We Are: At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About the team: OKX data team is responsible for the whole data scope of OKG, from techincal selection, architecture design, data ingestion, data storage, ETL, data visualisation to business intelligence and data science. We are data engineers, data analysts and data scientists. The team has end-to-end ownership of most of the data at OKx throughout the whole data lifecycle including data ingestion, data ETL, data warehouse and data services.  As a data engineer of the team, you will work with the team to leverage data technologies to empower evidence-based decision-making and improve the quality of the company's products and services. Responsibilities: Design and develop internal Data Platform components, including Data Governance center, Data Integration tools, job scheduling, and approval workflows. Build and maintain scalable backend services with high availability. Integrate with Data Warehouse, metadata, and job orchestration systems (e.g., Airflow, Flink , Spark). Develop Data Governance features such as data lineage, data quality, and access control. Write clean, maintainable code and technical documentation. Support system deployment, monitoring, and troubleshooting Requirements: At least 6 of more years of experience in a Software Engineering or Data Engineering related field Proficient in Java , Spring Boot, MyBatis/JPA, and RESTful API design. Solid experience with databases (MySQL, PostgreSQL) and distributed systems (Redis, Kafka ). Experience in data platforms, metadata, or workflow systems is a strong plus. Familiar with AWS or Alibaba cloud environments. Strong problem-solving skills and ability to take ownership of system modules. Good to have: Prior experience in Data Platform development or Data Governance systems Perks & Benefits: Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .