About The Role 

With millions of users worldwide, our products have earned a reputation for "just working" seamlessly right out of the box, almost like magic. This seamless experience is no accident; it's a testament to our commitment to creating products that are not just intuitive but downright obvious. At the heart of this commitment is the Roku OS QA Team, dedicated to rigorously testing every product and feature to ensure we deliver the most reliable streaming media platform in the industry.

Our mission is simple: help people effortlessly find and stream the content they love. We achieve this through cutting-edge technology and engineering, always putting the customer at the center of everything we do.

About the Team

As part of our team, you'll leverage your diverse skills to support both Software Engineers and QA Engineers, tackling the daily challenges of their roles. Your specialist knowledge, combined with the use of AI technologies, will be invaluable in suggesting improvements to enhance quality and streamline workflows, ensuring we continue to exceed our customers' expectations.

What you'll be doing

• Contribute to tools and technology
• Design, develop, and maintain AI-driven automation systems
• Collaborate with data scientists, software engineers, and product teams to understand and deliver AI-based solutions.
• Build new tools and technology
• Debug failing tests to improve the quality of automated test tools and frameworks
• Conduct code reviews for improve code quality and optimization
• Promote coding conventions and standards for code re-usability and cleanliness
• Assist in monitoring and maintenance of critical systems

We're excited if you have

• 3+ years of hands-on experience with automation systems
• 3+ years of Python programming experience
• 2+ years of experience developing test plans and test cases
• Ability to write simple Python scripts to preprocess data or interact with ML APIs.
• Bachelor’s degree in Computer Science or related
• Excellent verbal and written communication skills
• Experience working with remote teams
• Some knowledge of continuous integration tools (Jenkins/Hudson, TeamCity, Maven, Gradle)
• Hands on experience and proficiency in Linux/Unix systems
• Ability to learn new technologies quickly
• A self-directed professional able to work independently
• Previous experience with Non-Functional Testing (Performance Testing, Stress Testing)

#LI-AB3

About the team

With so many people using Roku’s products globally, we’ve become well-known for products that “just work” right out of the box and integrate almost by magic.  That doesn’t happen by accident, which is why we are committed to making sure our products aren’t just intuitive; they’re obvious.  To support that commitment, the Roku’s Automation support and Tools team focuses on providing innovative and impactful tools that improve efficiency, enhance productivity of all engineering to test Roku products, from industry’s most reliable streaming media platform to smart home products that seamlessly integrate with Roku entertainment OS for a great connected home user experience. We accomplish this using state of the art technology and engineering to make it happen, with consideration for the customer as the centre of all that we do.

Roku’s embedded software automation and tools team has an excellent opportunity for a Senior Software Engineer with strong experience in building automation framework and tools for embedded devices. The role involves developing and maintaining software and tools that help various internal teams to test and manage Roku’s products. Working closely with internal stakeholders to enhance existing automation toolset with new capabilities and advanced features that empower all engineering and accelerate validation efforts for SW releases. 

About the role

You will work cross-functionally with various engineering teams, using your automation tooling expertise to help both firmware developers and QA to create and deliver the highest quality products that provide valuable end-user feedback to improve customer experience. This position requires Python expertise with strong experience using web frameworks, excellent debugging, written, and organizational skills. You will be joining a talented, high-performance team of developers with a history of delivery. We are looking for someone who can help us maintain this pace and continue delivering high quality as we grow. 

We are looking for a keen problem solver and a self-motivated individual with excellent communication and collaborative skills who is eager to learn and grow in the consumer electronics space. As an engineer on the team, you will require the skills and confidence to undertake the challenges of working in a fast-paced environment, frequently be taken out of your comfort zone, and relish getting your hands dirty working with user-facing products. 

What you will be doing:

• Develop and release new E2E automation support and tools 
• Debug issues to improve the quality of automated test tools and frameworks 
• Conduct code reviews to improve code quality and optimization 
• Promote coding conventions and standards for code re-usability and cleanliness 
• Document feature guides, identify and formulate user requirements, and define product behavior 
• Support and maintain existing automation tools and technology 
• Mentor less experienced engineers and drive automation development 
• Assist in monitoring and maintenance of critical systems 
• Champion the adoption of AI tools and technologies to enhance automation capabilities and team productivity. 
• Review and provide technical feedback on design documents and high-level architecture diagrams across multiple tools and teams, with a focus on evaluating design trade-offs, scalability, maintainability, and alignment with overall system architecture. 

We're excited if you have:

• 10+ years of hands-on experience with automation systems 
• 10+ years of programming experience, preferably with Python 
• Bachelor’s degree in computer science or related field 
• Proficient in Linux, Python-based test automation frameworks, and tools using REST APIs 
• Hands-on experience in development/integration of E2E test automation frameworks and tools for embedded software devices 
• Proficient use of AI tools and technologies with a proven track record as a promoter and advocate for AI adoption in software development and testing automation. 
• Agentic workflow familiarity: Working knowledge of multi-step AI orchestration frameworks and the practical use of AI agents to support and streamline day-to-day development workflows. 
• Experienced in developing and maintaining web-based tools using JavaScript and React/Next.js 
• Experience with DevOps and continuous integration tools (Jenkins, GitLab CI, Docker, and Kubernetes) 
• Experience with CI/CD pipeline development and deployment via AWS or GCP cloud technologies 
• Experience with unit testing frameworks – pytest/pyunit and Cypress for UI testing 
• Experience developing web applications using Flask, FastAPI, Django, and Nginx 
• Knowledge in using AI for increasing test automation coverage and productivity 
• Experience with retail Consumer Electronic (CE) devices, ideally in the Over The Top (OTT) streaming domain 
• Expert problem-solving and technical troubleshooting skills 
• Ability to learn new technologies quickly 
• A self-directed professional able to work independently 
• Ability to work through ambiguous requirements and be flexible/adaptable to change 
• Comfortable and experienced working with cross-functional peers and internal stakeholders across European and US time zones 
• Excellent communication and collaborative skills 

Additional nice to have skills: 

• Previous experience with Non-Functional Testing (Performance Testing, Stress Testing) 
• Knowledge of network technologies and libraries such as TCP/IP and HTTP 
• Experience with database technologies (MySQL, PostgreSQL, MongoDB, Redis) for test data management 
• Familiarity with monitoring and observability tools (Grafana, Prometheus, ELK stack, Datadog) 
• Knowledge of streaming protocols and technologies (HLS, DASH, RTMP, WebRTC) 
• Experience with API testing tools (Postman, REST Assured, GraphQL) 
• Understanding of security testing principles and tools (OWASP, penetration testing) 
• Experience with mobile testing frameworks and cross-platform testing 
• Familiarity with test reporting and analytics platforms (Allure, TestRail, ReportPortal) 
• Experience with infrastructure as code (Terraform, Ansible, CloudFormation) 
• Knowledge of machine learning concepts for test optimization and predictive analysis 
• Familiarity with Agile/Scrum methodologies and project management tools (Jira, Confluence) 
• Basic understanding of hardware debugging tools and techniques for embedded systems 

#LI-AB3

About the Team 

The DMP team plays a critical role in Roku’s Advertising organization, leading initiatives around audience management that power decision-making across the advertising ecosystem. We develop and manage products that enable advanced segmentation and audience management for advertisers while meeting the operational needs of internal teams. 

We work closely with Product Managers, Machine Learning, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven capabilities to further enhance the effectiveness of advertising campaigns and improve operational efficiency of our platforms. 

About the Role 

We are seeking a highly skilled Senior Software Engineer with deep expertise in big data technologies, including Apache Spark and Apache Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products and APIs that power critical capabilities across the advertising platform. You will work with technologies such as Apache Spark, Apache Airflow, ScyllaDB/Cassandra, Aerospike, Kubernetes, and SpringBoot to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building high-scale data services and a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and audience management workflows. 

• Write clean, maintainable, and efficient code, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries using Apache Spark for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

API and Platform Development

• Design, Development, and maintain large scale, low latency API systems using SpringBoot and Kubernetes

• Maintain NoSQL Infrastructure including ScyllaDB and Aerospike

Collaboration & Mentorship 

• Partner with the machine learning team, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following ScyllaDB and Aerospike (preferred). 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Exceptional problem-solving abilities and the capacity to work independently or collaboratively. 

• Excellent verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and audience management. (preferred)

• Strong programming skills in Python, Java, and/or Scala. (preferred) 

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Jenkins & Terraform). (preferred) 

• Expertise in data modeling, schema design, and data visualization tools. Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred) 

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

#LI-GL1

About the Team 

The DMP team plays a critical role in Roku’s Advertising organization, leading initiatives around audience management that power decision-making across the advertising ecosystem. We develop and manage products that enable advanced segmentation and audience management for advertisers while meeting the operational needs of internal teams. 

We work closely with Product Managers, Machine Learning, Ad Sales, Ads Operations, and multiple groups within Advertising Engineering to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven capabilities to further enhance the effectiveness of advertising campaigns and improve operational efficiency of our platforms. 

About the Role 

We are seeking a highly skilled Senior Software Engineer with deep expertise in big data technologies, including Apache Spark and Apache Airflow. This hybrid position bridges software engineering and data engineering, requiring the ability to design, build, and maintain scalable systems for both application development and large-scale data processing. 

In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products and APIs that power critical capabilities across the advertising platform. You will work with technologies such as Apache Spark, Apache Airflow, ScyllaDB/Cassandra, Aerospike, Kubernetes, and SpringBoot to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building high-scale data services and a dedication to delivering exceptional results. 

What You’ll Be Doing 

Software Development 

• Design and build APIs and backend services using Spring Boot to support data products and audience management workflows. 

• Write clean, maintainable, and efficient code, ensuring adherence to best practices through code reviews. 

Big Data Engineering 

• Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and Apache Airflow. 

• Optimize data storage, retrieval, and processing systems to ensure reliability, scalability, and performance. 

• Develop and fine-tune complex queries using Apache Spark for large-scale datasets. 

• Monitor, troubleshoot, and improve data systems to minimize downtime and maximize efficiency. 

API and Platform Development

• Design, Development, and maintain large scale, low latency API systems using SpringBoot and Kubernetes

• Maintain NoSQL Infrastructure including ScyllaDB and Aerospike

Collaboration & Mentorship 

• Partner with the machine learning team, software engineers, and other teams to deliver integrated, high-quality solutions. 

• Provide technical guidance and mentorship to junior engineers, promoting best practices in software and data engineering. 

We’re Excited If You Have 

• 8+ years of experience in software and/or data engineering with expertise in big data technologies such as Apache Spark, Apache Airflow. 

• Expertise with at least one of the following ScyllaDB and Aerospike (preferred). 

• Strong understanding of SOLID principles and distributed systems architecture. 

• Proven experience in distributed data processing, data warehousing, and real-time data pipelines. 

• Advanced SQL skills, with expertise in query optimization for large datasets. 

• Exceptional problem-solving abilities and the capacity to work independently or collaboratively. 

• Excellent verbal and written communication skills. 

• Experience with cloud platforms such as AWS, GCP, or Azure, and containerization tools like Docker and Kubernetes. (preferred) 

• Experience in AdTech, in advertising data platforms and audience management. (preferred)

• Strong programming skills in Python, Java, and/or Scala. (preferred) 

• Knowledge of CI/CD pipelines, DevOps practices, and infrastructure-as-code tools (e.g., Jenkins & Terraform). (preferred) 

• Expertise in data modeling, schema design, and data visualization tools. Experience with building Agentic AI systems to automate decision-making and enhance analytics workflows. (preferred) 

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience). 

#LI-GL1

About the team

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers and Roku. The systems and solutions span across different disciplines and technologies to perform realtime multi-objective optimization with distributed systems at large scale and low latencies. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the entire landscape which we continuously evolve over time.

About the role 

In this role you will build teams focused on the Ads Auction and Marketplace to optimize yield, gross profit, perform realtime multi-objective optimization across various short and long term objectives, build control and simulation systems, design and run experiments and extend the experimentation framework. 

You will partner closely with other Engineering, Inventory and Product teams to define the vision and strategy for your group and to build and deliver the roadmap.

What you’ll be doing

• Lead the design, implementation, and evolution of real-time ads auction systems powering Roku’s CTV advertising across The Roku Channel and the Roku platform.
• Own and enhance core auction capabilities including ad pod construction, bid evaluation, ranking, pricing, pacing, budget enforcement, and frequency capping.
• Build low-latency, highly reliable distributed services that operate at massive scale, serving billions of ad opportunities with strict latency and uptime requirements.
• Design auction logic that balances viewer experience (ad load, relevance, repetition) with advertiser performance, publisher yield, and platform revenue.
• Develop and optimize SSP-side auction mechanisms, integrating with multiple DSPs, programmatic demand sources, and direct-sold campaigns.
• Partner closely with product managers, data science, ads research teams to translate marketplace and monetization goals into scalable technical solutions.
• Drive yield optimization through auction design, demand shaping, floor strategies, and pricing experiments.
• Lead experimentation using A/B testing, auction simulations, and offline replay frameworks, and make data-driven decisions based on performance metrics and statistical rigor.
• Ensure auction correctness, fairness, explainability, and transparency, while maintaining compliance with privacy, regulatory, and brand-safety requirements.
• Influence the long-term technical roadmap for Roku Ads by proposing architecture improvements, scalability strategies, and performance optimizations.

We are excited if you have

• 5+ years of experience building large-scale distributed systems
• 5+ years working with cloud-based platforms and infrastructure
• Deep experience in building microservices using Java for container platforms such as Docker or Kubernetes
• Solid understanding of databases SQL and NoSQL
• Hands-on Experience working with AWS, GCP or similar cloud services
• Experience with a breadth of protocols and data formats such as REST, WebSockets, HTTPS, JSON, and Protobuf
• Demonstrated ability to drive timely consensus in design with other senior team members
• Bachelors or Master's degree in Computer Science, Engineering, or equivalent

#LI-MS3

About the team

The Advertising Performance group focuses on performance for all participants in the Advertising ecosystem - Advertisers, Publishers and Roku. The systems and solutions span across different disciplines and technologies to perform realtime multi-objective optimization with distributed systems at large scale and low latencies. We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems and Auction Dynamics to solve a large set of complex problems. At the core of this is our Machine Learning, Experimentation and Inference Platform that powers the entire landscape which we continuously evolve over time.

About the role 

In this role you will build teams focused on the Ads Auction and Marketplace to optimize yield, gross profit, perform realtime multi-objective optimization across various short and long term objectives, build control and simulation systems, design and run experiments and extend the experimentation framework. 

You will partner closely with other Engineering, Inventory and Product teams to define the vision and strategy for your group and to build and deliver the roadmap.

What you’ll be doing

• Lead the design, implementation, and evolution of real-time ads auction systems powering Roku’s CTV advertising across The Roku Channel and the Roku platform.
• Own and enhance core auction capabilities including ad pod construction, bid evaluation, ranking, pricing, pacing, budget enforcement, and frequency capping.
• Build low-latency, highly reliable distributed services that operate at massive scale, serving billions of ad opportunities with strict latency and uptime requirements.
• Design auction logic that balances viewer experience (ad load, relevance, repetition) with advertiser performance, publisher yield, and platform revenue.
• Develop and optimize SSP-side auction mechanisms, integrating with multiple DSPs, programmatic demand sources, and direct-sold campaigns.
• Partner closely with product managers, data science, ads research teams to translate marketplace and monetization goals into scalable technical solutions.
• Drive yield optimization through auction design, demand shaping, floor strategies, and pricing experiments.
• Lead experimentation using A/B testing, auction simulations, and offline replay frameworks, and make data-driven decisions based on performance metrics and statistical rigor.
• Ensure auction correctness, fairness, explainability, and transparency, while maintaining compliance with privacy, regulatory, and brand-safety requirements.
• Influence the long-term technical roadmap for Roku Ads by proposing architecture improvements, scalability strategies, and performance optimizations.

We are excited if you have

• 5+ years of experience building large-scale distributed systems
• 5+ years working with cloud-based platforms and infrastructure
• Deep experience in building microservices using Java for container platforms such as Docker or Kubernetes
• Solid understanding of databases SQL and NoSQL
• Hands-on Experience working with AWS, GCP or similar cloud services
• Experience with a breadth of protocols and data formats such as REST, WebSockets, HTTPS, JSON, and Protobuf
• Demonstrated ability to drive timely consensus in design with other senior team members
• Bachelors or Master's degree in Computer Science, Engineering, or equivalent

#LI-MS3

About The Role 

With millions of users worldwide, our products have earned a reputation for "just working" seamlessly right out of the box, almost like magic. This seamless experience is no accident; it's a testament to our commitment to creating products that are not just intuitive but downright obvious. At the heart of this commitment is the Roku OS QA Team, dedicated to rigorously testing every product and feature to ensure we deliver the most reliable streaming media platform in the industry.

Our mission is simple: help people effortlessly find and stream the content they love. We achieve this through cutting-edge technology and engineering, always putting the customer at the center of everything we do.

About the Team

As part of our team, you'll leverage your diverse skills to support both Software Engineers and QA Engineers, tackling the daily challenges of their roles. Your specialist knowledge will be invaluable in suggesting improvements to enhance quality and streamline workflows, ensuring we continue to exceed our customers' expectations.

As a Senior Software Engineer (SDET), you'll be the transformational force that revolutionizes our testing approach. You'll leverage AI and advanced analytics to identify quality gaps, architect intelligent testing solutions, and establish new standards for test effectiveness that go beyond simple coverage metrics.

What you'll be doing

• Design and implement intelligent test analysis systems that identify quality gaps, predict failure patterns, and optimize test effectiveness
• Design systems that collect, analyse and act on the testing data to continuously improve on the quality processes
• Experience with systematic regression tracking and implementing process to prevent regression reoccurrence
• Establish new methodologies for measuring and improving test quality beyond simple pass/fail metrics, focusing on regression prevention and production reliability 
• Leverage AI-powered tools for automated failure analysis, root cause identification, and test flakiness scoring
• Define and implement architectural patterns that make testing more effective, maintainable, and aligned with business impact

We're excited if you have

• 5+ years of hands-on experience with test architecture and automation systems design
• 8+ years of programming experience across multiple languages with Python
• Proven track record in driving test transformation: Experience leading initiatives that significantly improved test effectiveness and reduced production issues
• AI expertise for testing: Ability to design, implement, and optimize solutions leveraging LLMs, and predictive analytics for quality assurance
• Knowledge of continuous integration tools (Jenkins/GitLab, TeamCity, AWS) and their optimization for quality gates
• Advanced test analysis skills: Experience with test flakiness analysis, failure pattern recognition, and automated root cause identification
• Excellent verbal and written communication skills with ability to influence senior leadership and cross functional teams on quality initiatives
• Some working knowledge of C++
• Leadership experience mentoring engineers and driving organizational change in testing practices
• Certifications or training in AI/ML or AI testing (e.g., Coursera AI for Everyone, Google AI Engineer, ISTQB AI Testing Foundation)

#LI-AB3

About the Team

Join a team dedicated to delivering customer-focused features that elevate user experiences on a global scale. Our team specializes in creating engaging content such as wallpapers, screensavers, trivia, featured experiences, AI project for content generations, and more. Guided by an ambitious product roadmap, we aim to accelerate growth and scale by introducing innovative features to millions of users worldwide.

We foster a culture of ownership where developers and engineers are self-motivated to tackle challenges and ship impactful solutions. Collaboration is key—engineers work closely with cross-functional teams, including UI design, product management, and business leadership, to make things happen. If you’re passionate about reimagining the world of streaming media in a dynamic, collaborative environment, this is the team for you.

About the Role

Our products are known for their seamless integration and intuitive design that delights users right out of the box. These qualities are the result of meticulous engineering and a commitment to excellence.

As part of the engineering team, you’ll develop and manage features for Screensavers, Static & Dynamic Wallpapers, Trivia, Featured Experience and AI initiatives. You will be working on A.I initiatives to develop new features on platforms to create user enhancing experiments.

  
What You’ll Be Doing

• Designing and developing features for new Experiences on the Roku platform. 
• Creating PoC to elaborate on ideas and work in startup mindset to break fast and deliver quickly. 
• Collaborating with UI/UX design and backend team to create and implement new experiences. 
• Adapting PoCs for productionising the solution
• Investigating, diagnosing, and resolving issues to maintain commercially viable solutions. 

We Are Excited If You Have

•  At least 10yrs experience in a Software Engineering environment
• Substantial Project based on using AI/ML and LLM technologies
• Proficiency in scripting languages such as JavaScript, TypeScript, React Native, Python, BrightScript, or related technologies. 
• Experience working in an embedded environment 
• Consumer electronics experience in media/content or ad product development is a plus. 
• Experience in productionizing solutions, including content management, UI development, cloud development, and cloud backend integration. 
• Knowledge of Core OS concepts like memory management and multi-threading. 
• Experience in API design, with an understanding of considerations and trade-offs. 
• Strong communication skills, as this role involves frequent collaboration across teams.
• Bachelor’s or Master’s degree in Computer Science or a related field

#LI-NM1

About the team

At Roku, the Device Monetization and Themed Experiences (DMTE) team, a part of the Advertising organization, is where the magic behind the scenes happens. We’re the engineers who build the high-performance graphics and UI foundations that power the FRAME engine — the core technology enabling Roku’s smooth, responsive, and visually rich experiences on millions of devices worldwide. Our work lives in the middleware and UI layers, and its impact is felt every time a user navigates a menu, enjoys an animated ad, or is wowed by the bespoke experience built to market the latest TV show or Movies. We thrive on solving technical challenges — from optimizing UI rendering to fine-tuning memory usage — using BrightScript (or JavaScript-like) to deliver rock-solid, high-performance solutions. We work in a collaborative, high-trust environment where great ideas can come from anywhere, partnering closely with firmware, UI, and product teams to ensure our platform is lightning fast, reliable, and ready for the next generation of streaming innovation. If you love building the invisible foundations that make great user experiences possible, this is the team for you.

About the role

As a Software Engineer in the DMTE team, you’ll contribute to Roku’s platform innovation — implementing and optimizing BrightScript (or JavaScript-like) systems for graphics rendering and the FRAME engine. You’ll tackle performance-critical challenges, ensuring our devices deliver smooth visuals and instant responsiveness at scale. You’ll have the opportunity to learn about core architecture, work across the stack with hardware, firmware, and application teams, and see your work directly impact tens of millions of users. This is a role for engineers who love technical problem-solving, care about performance, and want to work on technology that quietly powers an entire ecosystem. If you’re ready to learn, grow, and contribute to the future of streaming, we’d love to hear from you.

What you'll be doing

• Build scalable UI features optimized for millions of users
• Contribute to technical investigations and solutions for middleware and UI challenges
• Explore integrating AI/ML capabilities and leverage generative AI tools to accelerate development
• Collaborate with cross-functional teams on global platform features
• Develop engineering tools and learn from experienced developers
• Stay current with AI trends and emerging technologies

We're excited if you have

• 3+ years software engineering experience with UI development exposure
• C++ in an embedded environment
• Proficiency in BrightScript (or JavaScript-like) skills plus some experience with Python
• Strong problem-solving and technical communication abilities
• Interest in AI applications and a willingness to learn about generative AI tools
• Proactive mindset with passion for continuous learning and fast iteration

#LI-NM1

About the Team

The Advanced Development team at Roku pushes beyond today’s product lines to invent the next generation of intelligent and generative media systems.
We explore ideas that sit years ahead of production, developing foundational technologies that will redefine how content is understood, created, and personalised across millions of Roku devices.

This is a rare environment — a PhD-level, cross-disciplinary group combining machine learning research, software engineering, and DevOps.
Everyone here is an expert, but not narrowly focused. The team blends deep technical mastery with broad creative vision — people who challenge convention, embrace ambiguity, and build what’s never been built before. It’s a collaborative, low-ego, ownership-driven culture built on trust and curiosity.

We’re seeking an Applied Scientist with a strong foundation in mathematics, machine learning, and computer science, combined with experience in cloud engineering, DevOps, and computer vision — someone who thrives where research meets production.

About the Role

As a Senior Applied Machine Learning Engineer, you’ll help design, build, and deploy the systems that make media smarter.
You’ll work across the full model and software lifecycle, from prototype to production, developing scalable ML pipelines and cloud architectures that power generative AI, intelligent media understanding, content analysis, and advertising intelligence.

You’ll operate at the intersection of machine learning, infrastructure, and software engineering, taking ownership from data collection through deployment — and seeing your work directly influence how audiences experience Roku’s content and advertising ecosystem.

What You’ll Be Doing

• Deploying scalable, fault-tolerant computer vision, media understanding, and generative AI systems to production

• Overseeing the full model development cycle: ideation, prototyping, implementation, deployment, testing, and operations

• Designing uncertainty metrics and communicating results to both technical and non-technical stakeholders

• Gathering and compiling datasets, defining annotation ontologies, auditing annotation operations, and ensuring data quality

• Staying up to date with industry and academic trends in computer vision, machine learning, and generative models for media and advertising

• Working closely with product and other engineering teams to implement new content and advertising experiences through cloud services

• Integrating services from other teams around the company, while also providing reusable ML services to others

• Evaluating and providing feedback on new platform technologies provided by internal teams

• Working with QA teams to address bugs and contribute to automation and quality assurance

We’re Excited If You Have

• A Master’s degree (PhD preferred) in Computer Science, Applied Mathematics, or a related field

• Strong background developing applied machine learning systems using PyTorch or TensorFlow

• Expertise in image processing, computer vision, or natural language processing

• Experience using AWS, GCP, or Azure for storing data, training, and serving models

• Proven ability to evaluate models and communicate insights effectively

• Experience building APIs with frameworks such as GraphQL or REST

• Experience with workflow orchestration tools such as Airflow, Argo, AWS Step Functions, or Metaflow

• Hands-on experience with Docker, Kubernetes, Terraform, CloudFormation, CI/CD automation, and Python build or packaging tools

#LI-PA1

About the team

At Roku, the Device Monetization and Themed Experiences (DMTE) team, a part of the Advertising organization, is where the magic behind the scenes happens. We’re the engineers who build the high-performance graphics and UI foundations that power the FRAME engine — the core technology enabling Roku’s smooth, responsive, and visually rich experiences on millions of devices worldwide. Our work lives in the middleware and UI layers, and its impact is felt every time a user navigates a menu, enjoys an animated ad, or is wowed by the bespoke experience built to market the latest TV show or Movies. We thrive on solving the toughest technical challenges — from optimizing UI rendering to fine-tuning memory usage — using BrightScript (or JavaScript-like) to deliver rock-solid, high-performance solutions. We work in a collaborative, high-trust environment where great ideas can come from anywhere, partnering closely with firmware, UI, and product teams to ensure our platform is lightning fast, reliable, and ready for the next generation of streaming innovation. If you love building the invisible foundations that make great user experiences possible, this is the team for you.

About the role

As a Senior Software Engineer in the DMTE team, you’ll be at the heart of Roku’s platform innovation — designing, implementing, and optimizing BrightScript (or JavaScript-like) systems for graphics rendering and the FRAME engine. You’ll take on complex, performance-critical challenges that demand both creativity and precision, ensuring our devices deliver buttery-smooth visuals and instant responsiveness at scale. You’ll have the opportunity to shape core architecture, work across the stack with hardware, firmware, and application teams, and see your work directly impact tens of millions of users. This is a role for engineers who love deep technical problem-solving, care about performance down to the last millisecond, and want to work on technology that quietly powers an entire ecosystem. If you’re ready to push boundaries, mentor others, and help define the future of streaming, we’d love to hear from you.

What you'll be doing

• Build scalable UI features optimized for millions of users
• Lead technical investigations and architect solutions for complex middleware and UI challenges
• Integrate AI/ML capabilities and leverage generative AI tools to accelerate development
• Collaborate with cross-functional teams on global platform features
• Develop engineering tools and mentor junior developers
• Stay current with AI trends and emerging technologies

We're excited if you have

• 5+ years software engineering experience with UI development expertise
• Advanced BrightScript (or JavaScript-like) skills plus proficiency in Python
• Strong root cause analysis and technical communication abilities
• Knowledge of AI applications and experience with generative AI tools
• Proactive mindset with passion for continuous learning and fast iteration

#LI-NM1

About the team

At Roku, the Device Monetization and Themed Experiences (DMTE) team, a part of the Advertising organization, is where the magic behind the scenes happens. We’re the engineers who build the high-performance graphics and UI foundations that power the FRAME engine — the core technology enabling Roku’s smooth, responsive, and visually rich experiences on millions of devices worldwide. Our work lives in the middleware and UI layers, and its impact is felt every time a user navigates a menu, enjoys an animated ad, or is wowed by the bespoke experience built to market the latest TV show or Movies. We thrive on solving the toughest technical challenges — from optimizing UI rendering to fine-tuning memory usage — using BrightScript (or JavaScript-like) to deliver rock-solid, high-performance solutions. We work in a collaborative, high-trust environment where great ideas can come from anywhere, partnering closely with firmware, UI, and product teams to ensure our platform is lightning fast, reliable, and ready for the next generation of streaming innovation. If you love building the invisible foundations that make great user experiences possible, this is the team for you.

About the role

As a Senior Software Engineer in the DMTE team, you’ll be at the heart of Roku’s platform innovation — designing, implementing, and optimizing BrightScript (or JavaScript-like) systems for graphics rendering and the FRAME engine. You’ll take on complex, performance-critical challenges that demand both creativity and precision, ensuring our devices deliver buttery-smooth visuals and instant responsiveness at scale. You’ll have the opportunity to shape core architecture, work across the stack with hardware, firmware, and application teams, and see your work directly impact tens of millions of users. This is a role for engineers who love deep technical problem-solving, care about performance down to the last millisecond, and want to work on technology that quietly powers an entire ecosystem. If you’re ready to push boundaries, mentor others, and help define the future of streaming, we’d love to hear from you.

What you'll be doing

• Build scalable UI features optimized for millions of users
• Lead technical investigations and architect solutions for complex middleware and UI challenges
• Integrate AI/ML capabilities and leverage generative AI tools to accelerate development
• Collaborate with cross-functional teams on global platform features
• Develop engineering tools and mentor junior developers
• Stay current with AI trends and emerging technologies

We're excited if you have

• 5+ years software engineering experience with UI development expertise
• C++ experience in an embedded environment
• Advanced BrightScript (or JavaScript-like) skills plus proficiency in Python
• Strong root cause analysis and technical communication abilities
• Knowledge of AI applications and experience with generative AI tools
• Proactive mindset with passion for continuous learning and fast iteration

#LI-NM1

Why Verifone

For more than 30 years, Verifone has established a remarkable record of leadership in the electronic payment technology industry. Verifone is one of the leading electronic payment solutions brands and among the largest providers of electronic payment systems worldwide.

Verifone has a diverse, dynamic, and fast-paced work environment in which employees are focused on results and have opportunities to excel. We take pride in working with leading retailers, merchants, banks, and third-party partners to invent and deliver innovative payment solutions around the world. We strive for excellence in our products and services and are obsessed with customer happiness.

Across the globe, Verifone employees are leading the payments industry through experience, innovation, and an ambitious spirit. Whether it’s developing the next generation of secure payment systems or finding new ways to bring electronic payments to emerging markets, the Verifone team is dedicated to the success of our customers, partners, and investors. It is this passion for innovation that drives every Verifone employee toward personal and professional success.

Verifone is proudly an in-office work culture as we see immense benefits to career development and business results from our colleagues being physically co-located.

What’s Exciting About the Role

Verifone is seeking a Kafka DevOps Engineer to join our Platform Engineering team. This is an operations-first role with a strong emphasis on scripting, automation, and pipeline development. You’ll be hands-on with day-to-day Kafka operations, reliability, tuning, and high availability for payment gateway solutions that process billions of transactions annually on-prem and in AWS Cloud. Beyond keeping the lights on, you’ll play a key role in building the data pipelines—of which Kafka is a core component—that power Verifone’s new AI, machine learning, and analytics initiatives. You’ll also be part of an active effort to migrate Kafka and related services to Kubernetes, giving you hands-on experience with a meaningful infrastructure modernization project. The technology footprint is broad: Redis, MongoDB, PostgreSQL, MySQL, Snowflake, and more—so you’ll grow well beyond a single-technology niche.

Key Responsibilities

Kafka Operations & Reliability

• Manage and support Apache Kafka clusters (including MSK), Kafka Connect ecosystem, and KSQL for high-throughput, fault-tolerant messaging and event streaming pipelines.
• Monitor system health, set up alerts, and drive incident response and root cause analysis (RCA).
• Handle day-to-day operational tasks including offset management, lag monitoring, consumer group management, and cluster rebalancing.
• Perform routine cluster maintenance: upgrades, configuration changes, scaling, and health checks.

Scripting, Automation & DevOps

• Develop and manage automation scripts using Python and Shell scripting to reduce manual toil and improve operational efficiency.
• Design, implement, and maintain robust CI/CD pipelines for patching automation.
• Build and maintain Infrastructure as Code (IaC) using tools such as Terraform, Ansible, or similar.
• Containerize and orchestrate workloads using Docker and Kubernetes, with the opportunity to help migrate Kafka and related services to Kubernetes.

Data Pipeline Development

• Build and optimize end-to-end data pipelines, with Kafka as a core streaming component alongside batch and ETL processes, enabling new AI, ML, and analytics use cases.
• Collaborate with development teams to implement best practices for data flow, security, scalability, and performance.
• Continuously identify and implement improvements to the software development lifecycle (SDLC).

Cloud & Infrastructure

• Manage cloud infrastructure on AWS (VMs, networking, storage, IAM, etc.).
• Support cloud migration tasks and assist in moving workloads between on-prem and cloud environments.

Required Qualifications / Skills

• 4+ years of overall engineering experience with 2+ years of hands-on experience supporting Kafka infrastructure in a large-scale production environment.
• Kafka Producer/Consumer microservices concepts and Kafka distributed architecture.
• Solid Linux fundamentals: networking basics, logs, system troubleshooting, process/memory, disk.
• Strong scripting and automation skills (Python, Bash) with a track record of reducing operational toil.
• CI/CD pipeline development and Infrastructure-as-Code experience (Terraform preferred).
• Cloud engineering skills, preferably AWS (EC2, VPC, IAM, MSK/ElastiCache, CloudWatch).
• Familiarity with observability tools (metrics/logs/tracing concepts) and incident response practices.
• Basic understanding of distributed systems tradeoffs (availability, consistency, partitions, backpressure).
• Strong communication and presentation skills with emphasis on executive communication.
• Flexible with regards to working shifts; on-call and weekends.

Preferred Skills (Highly Desired)

Data Engineering & Pipelines

• Data engineering skills including data analytics, data processing, ETL, and data lake technologies (batch and streaming, file formats like Parquet, table formats like Iceberg/Delta/Hudi, basic orchestration).
• Experience with AWS data tools (Athena, Glue, Iceberg, Redshift, etc.).
• Exposure to Kafka Streams, Apache Flink, or similar stream processing frameworks.

Database & Caching Technologies

• Operate Redis deployments for caching, ephemeral state, queues/streams, and rate limiting use cases.
• Relational DB experience: PostgreSQL and/or MySQL (indexing basics, vacuum/analyze, query plans, replication fundamentals).
• MongoDB operational familiarity (replica sets, elections, oplog basics, backup/restore).

Infrastructure & Security

• Container/Kubernetes familiarity (deployments, stateful workloads, storage classes).
• On-prem experience (VMware/KVM, storage, networking).
• Security fundamentals: least privilege, secrets management, encryption-in-transit/at-rest concepts.
• Experience working with PCI (Payment Card Industry Data Security) standards.

What We Offer

• Direct impact on Verifone’s global payment infrastructure—your work keeps billions of transactions flowing reliably every year.
• Ground-floor involvement in building the data pipelines that will drive Verifone’s AI, machine learning, and analytics strategy.
• Hands-on participation in a Kafka-to-Kubernetes migration—a resume-building modernization project from day one.
• Multi-technology exposure—Kafka, Redis, MongoDB, PostgreSQL, MySQL, Snowflake—so you grow as a well-rounded platform engineer, not a single-tool specialist.
• Mentorship from senior engineers and Kafka architects with deep production experience.
• Clear career progression path from mid-level to senior and lead engineer.
• Funded certification paths—Confluent (CCDAK, Certified Administrator), AWS (Solutions Architect, MSK Specialty), CKA—plus budget for courses and technical conferences.
• Hybrid/remote working flexibility with a collaborative team culture.
• Competitive compensation with performance-based incentives.

Our Commitment

Verifone is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Verifone is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

This senior role focuses on strengthening the quality engineering foundation for our SDK by developing robust automation, scalable CI/CD systems, and effective test strategies. You will work closely with cross-functional partners to enhance test coverage, improve workflows, and ensure reliable delivery across multiple platforms. The role requires strong technical depth, collaborative working, and the ability to drive meaningful impact quickly.

What you’ll be doing

• Designing, implementing, and maintaining CI/CD pipelines to support build, test, and release workflows.
• Developing automation and tooling in Python to streamline test orchestration and system validation.
• Creating and running automated tests across unit, integration, and system layers.
• Debugging and diagnosing issues across build, test, and deployment environments.
• Supporting Linux and Windows development environments and contributing to cross-platform scripting.
• Applying modern test frameworks and quality metrics to improve test strategy and reporting.
• Collaborating closely with multiple SDK teams to align on shared initiatives.
• Participating in rotational assignments to deepen domain expertise and broaden cross-project knowledge.
• Coordinating with teams across London, Bristol, and Dublin, including occasional travel as needed.
• Mentoring peers, sharing best practices, and influencing quality engineering approaches.

What we are looking for

• Experience building and maintaining CI/CD pipelines (Jenkins/Groovy or equivalent).
• Strong Python 3 skills for automation, tooling, and test orchestration.
• Experience developing and executing automated tests at multiple levels.
• Fluency with Linux and Windows development environments.
• Proficiency with scripting languages such as python, bash, or PowerShell.
• Ability to diagnose and resolve issues across complex build and test systems.
• Familiarity with test frameworks such as pytest, GTest, or similar.
• Understanding of software quality metrics, reporting, and test strategy.
• Experience or awareness in one or more additional areas: C/C++, CMake, C#, Rust, .NET, Docker, Kubernetes, VM orchestration, graphics APIs, AIML/MLOps, or desktop app testing.
• Strong communication and collaboration skills, with the ability to work effectively across distributed teams and represent quality engineering perspectives.

The role

We are looking for an experienced Graphics engineer with experience in real time computer graphics or games to design and implement high-quality, game-like rendering scenarios to evaluate and showcase new graphics features.

The ideal candidate would have experience in real-time rendering, ideally with PlayStation 5 graphics APIs or comparable low-level console/modern graphics APIs.

The team

Based in London, our team are part of the ‘Foundational Systems and Experiences Engineering’ group. We build the low-level SDKs and fundamental technologies used by our game development partners to create PlayStation Games.

Our team are working on the latest GPU and Machine Learning technologies to deliver the next generation of high-performance computer graphics for PlayStation.

What you’ll be doing:

• Design and implement high-quality, game-like rendering scenarios to evaluate and showcase new graphics features.
• Develop production-grade sample code, libraries, and tools for both internal teams and inclusion in the PlayStation SDK.
• Collaborate with platform, tools, and studio teams worldwide to drive adoption and guidelines.
• Influence graphics feature design through hands-on prototyping and performance analysis.
• Contribute to clear, maintainable, developer-facing code and documentation.

What we’re looking for:

• Strong C/C++ with experience in game/game-engine development ( e.g. memory management, task management)
• Strong real-time rendering experience, ideally with PlayStation 5 graphics APIs or comparable low-level console/modern graphics APIs.
• Good understanding of GPU architecture and rendering pipelines.
• Proficiency in HLSL (Shader Model 6) and modern shader development practices.
• Strong debugging and performance analysis skills (CPU/GPU).
• Excellent collaboration skills, comfortable working with globally distributed teams.
• Working experience in development practices such as SCRUM and use of collaborative source control features in GitHub.
• Degree in Computer Science, Mathematics, or equivalent experience in the industry.

Nice to haves:

• Experience with global illumination, ray tracing, or advanced lighting techniques.
• Experience creating or editing game engines
• Experience building developer-facing samples, tools, or user documentation.
• An open source body of work in GitHub or similar.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

Role Description:

We are looking for an independent, dedicated Senior ML Engineer to join the Visual Computing Group (VCG) and contribute to redefining the world of game play and live streaming via advanced R&D. VCG’s mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency.

What you’ll be doing:

• Develop and improve core generative models for graphics and video processing for a variety of applications, such as live video streaming, game rendering, etc.
• Research and prototyping of new methods for graphics or video enhancement, and data generation pipelines from generative models
• Collaborate with team members on drafting publications and patent submissions
• Participate and assist the team in core R&D work with other teams within Sony Interactive Entertainment

What we’re looking for:

• PhD or MSc in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning, Computer Graphics or a related field, or equivalent skills evidenced by work experience in the specific domain of the post
• 5+ years of experience in demonstrable research experience in industry or academia.
• Strong background in: TensorFlow or PyTorch; Python and packages/libraries related to computer vision or graphics; evidenced by the development of advanced applications in image/video/graphics processing or computer vision (minimum of 3 years of experience for ML engineer, minimum 5 years for Senior ML engineer),
• Evidence of leading technical developments by at least 1 research publication in a top-tier conference like CVPR, ECCV, ICCV, SIGGRAPH or similar
• Solid background in one or more of the following:

(i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design;

(ii) design and test of advanced convolutional, recurrent, transformer-based, diffusion-based or other neural network architectures in a task-specific manner;

(iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or similar

Desired qualifications:

• Publications, e.g. in top-tier conferences and journals: IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, conferences like IEEE CVPR/ICCV/ECCV, NeurIPS, ICML, ICLR, or similar
• Some theoretical understanding of the graphics pipeline, including coordinate transformations between frames of reference, PBR materials, rasterization, lighting, and ray tracing
• Experience in image processing theory and methods, evidenced by the development of practical designs in this area
• Some experience with 3D engines such as Unreal or Unity; in particular, generation of datasets, extraction of G-buffers, motion vectors, etc.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

The role

We are looking for a Senior Graphics Engineer with strong experience in real-time computer graphics and game development to design and implement high-quality, game-like rendering scenarios that evaluate, validate, and showcase new graphics features.

In this role, you will drive technical direction through hands-on development, prototyping, and performance analysis, influencing the design and adoption of rendering technologies across teams.

The ideal candidate brings deep expertise in real-time rendering, ideally with PlayStation 5 graphics APIs or comparable low-level console or modern graphics APIs, and a proven ability to deliver robust, scalable solutions while collaborating effectively with globally distributed teams.

The team

Based in London, our team are part of the ‘Foundational Systems and Experiences Engineering’ group. We build the low-level SDKs and fundamental technologies used by our game development partners to create PlayStation Games.

Our team are working on the latest GPU and Machine Learning technologies to deliver the next generation of high-performance computer graphics for PlayStation.

What you’ll be doing

• Lead the design and development of high-quality, game-like rendering scenarios to evaluate, validate, and showcase new graphics features at scale.
• Own and deliver production-grade sample code, libraries, and tools for internal teams and inclusion in the PlayStation SDK, ensuring robustness, scalability, and long-term maintainability.
• Drive cross-team collaboration with platform, tools, developer support and studio teams globally to establish guidelines and enable successful adoption of new rendering technologies.
• Influence graphics feature direction through hands-on prototyping, deep technical investigation, and performance analysis across CPU and GPU.
• Define and uphold engineering standards for developer-facing code, ensuring clarity, usability, and high-quality documentation.
• Mentor other engineers and contribute to the technical growth of the team.

What we’re looking for

• 6–10+ years of professional experience in software engineering, with a strong focus on game development or real-time rendering.
• Expert-level C/C++ with significant experience in game or game engine development (e.g., memory systems, job systems, low-level optimization).
• Deep experience in real-time rendering, ideally with PlayStation 5 graphics APIs or comparable low-level console / modern graphics APIs (e.g., Vulkan, DirectX 12).
• Strong understanding of GPU architecture, rendering pipelines, and performance trade-offs across CPU/GPU boundaries.
• Advanced proficiency in HLSL (Shader Model 6) and modern shader development techniques.
• Proven ability to debug, profile, and optimize complex systems across CPU and GPU.
• Demonstrated ability to design systems and make sound technical trade-offs.
• Strong collaboration and communication skills, with experience working across globally distributed teams.
• Experience with modern development practices (e.g., SCRUM) and collaborative workflows using GitHub.
• Degree in Computer Science, Mathematics, or equivalent experience in a practical setting.

Nice to haves

• Experience architecting or significantly contributing to game engines or rendering frameworks.
• Experience developing and optimising advanced rendering techniques such as global illumination, ray tracing, or hybrid rendering approaches.
• Experience building high-quality developer-facing samples, tools, or user documentation used by external developers.
• Track record of technical leadership, including mentoring engineers or leading projects/features.
• Contributions to open source projects or a strong public technical portfolio (e.g., GitHub).

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

Role Description:

We are looking for an independent, dedicated Machine Learning Engineer/Senior ML Engineer to join the Visual Computing Group (VCG) and contribute to redefining the world of game play and live streaming via advanced R&D. VCG’s mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency.

What you’ll be doing:

• Develop and improve core generative models for graphics and video processing for a variety of applications, such as live video streaming, game rendering, etc.
• Research and prototyping of new methods for graphics or video enhancement, and data generation pipelines from generative models
• Collaborate with team members on drafting publications and patent submissions
• Participate and assist the team in core R&D work with other teams within Sony Interactive Entertainment

What we’re looking for:

• PhD or MSc in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning, Computer Graphics or a related field, or equivalent skills evidenced by work experience in the specific domain of the post
• 3+ years of experience in demonstrable research experience in industry or academia.
• Strong background in: TensorFlow or PyTorch; Python and packages/libraries related to computer vision or graphics; evidenced by the development of advanced applications in image/video/graphics processing or computer vision (minimum of 3 years of experience for ML engineer, minimum 5 years for Senior ML engineer),
• Evidence of leading technical developments by at least 1 research publication in a top-tier conference like CVPR, ECCV, ICCV, SIGGRAPH or similar
• Solid background in one or more of the following:

(i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design;

(ii) design and test of advanced convolutional, recurrent, transformer-based, diffusion-based or other neural network architectures in a task-specific manner;

(iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or similar

Desired qualifications:

• Publications, e.g. in top-tier conferences and journals: IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, conferences like IEEE CVPR/ICCV/ECCV, NeurIPS, ICML, ICLR, or similar
• Some theoretical understanding of the graphics pipeline, including coordinate transformations between frames of reference, PBR materials, rasterization, lighting, and ray tracing
• Experience in image processing theory and methods, evidenced by the development of practical designs in this area
• Some experience with 3D engines such as Unreal or Unity; in particular, generation of datasets, extraction of G-buffers, motion vectors, etc.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

About the Role

We’re looking for a Staff Software Engineer to build AI-powered tools and integrations that plug directly into game engines, editors, clients, and backend services. You’ll deliver high-quality C++ integrations across proprietary studio engines, ship robust build/QA automation, and partner with multiple PlayStation Studios teams to make AI an everyday part of development.

What You’ll Be Doing

• Build and maintain engine/editor plugins, runtime SDKs, and services that integrate AI (LLMs and related systems) into game clients, servers, and build tools.
• Ship performant, memory-aware C++ by profiling, optimizing, and debugging across PC/console builds with tight frame budgets.
• Design stable API surfaces for game teams (C++/C API, gRPC/HTTP) with versioning, telemetry, and backward compatibility.
• Stand up CI/CD for game builds and tools (UBT or proprietary build systems; artifact packaging; nightly/regression suites; distributed/accelerated builds).
• Automate QA for tooling and in-engine features using engine test frameworks and headless runs, and wire results into CI and dashboards.
• Implement production LLM integrations (prompting, RAG/tool calls, guardrails/safety, observability, timeouts/retries, and cost controls).
• Collaborate with studio engineering, tech art, design, and QA to land integrations across varied codebases and pipelines.
• Document patterns, provide sample projects, and deliver internal training so solutions scale across PlayStation Studios.
• Influence standards and tech choices for AI in our dev stack, and contribute to shared libraries and best practices.

Qualifications

• You have at least five years of experience building production software in modern C++ (C++17/20) with strong fundamentals in memory management, concurrency, performance, and debugging.
• You have shipped tools or runtime features in AAA engines, including work on plugins/modules, asset and build pipelines, and editor/runtime integration.
• You have delivered features or tooling that integrate with LLMs or other ML services, and you understand prompt design, evaluation, safety, and telemetry for production usage.
• You have implemented engine-level automated testing (functional and integration), including headless execution and CI gating.
• You work fluently with large code/asset repositories and are comfortable with both Perforce and Git.
• You communicate clearly across disciplines and translate diverse studio requirements into pragmatic, maintainable solutions.
• You write thorough documentation and favor well-tested, maintainable code.

Nice to Have

• You have built networking/service integrations for game backends (gRPC/HTTP) and implemented telemetry/observability (logs, metrics, traces).
• You have packaged SDKs/plugins for multiple studios and managed semantic versioning and migration tooling.
• You understand console platform requirements and certification workflows.
• You are familiar with security, privacy, and responsible-AI practices in production systems.

Please note; this position can be completed remotely from The UK

Experienced Deep Learning Engineer for Game Technology

We are looking for a machine learning engineer with a solid understanding of low-level systems programming. If you are as comfortable in the memory view of your debugger as you are with training networks to solve problems, we would love to hear from you.

This role could suit an experienced embedded/games industry programmer with a passion for Machine Learning, or an accomplished Machine Learning/Vision programmer with a good understanding of computer architecture and performance.

About the Advanced Technology Group

The Advanced Technology Group (ATG) is a part of Foundational Systems and Experiences Engineering (FSEE) within the Platform Business Group. Established over 20 years ago as part of PlayStation’s first party game development studios, ATG's focus has always been to help game developers to get the most out of PlayStation hardware, and this is still true today. The majority of the group holds responsibility for a large part of the GPU software stack used by all PlayStation games, which allows us to collaborate with engineering teams worldwide, from third party game developers to hardware vendors, to deliver key platform technologies.

You will be part of a small creative team within ATG, tackling problems centred around computer vision and machine learning. Examples of projects include a novel facial performance capture system used to produce assets for AAA games, and building a general purpose solution for on-console inference.

The Role

You will be expected to develop innovative ML solutions for deployment in games and in the development pipeline. This also involves making technology choices, prototype solutions and bringing them to production.

Some of these systems are expected to run on millions of PlayStations in people’s homes, making high run-time performance crucial. You should stay up to date with the competition and the industry’s latest advances and academic developments. The role also involves close collaboration with our other teams in Europe, the U.S and Japan, as well as technical communication of the ideas and solutions developed.

The Essential Requirements

• Experience with modern Deep Learning and Pytorch: You will be expected to make decisions about data and architectures, to implement pipelines for training and validation and to develop and deploy models in production.

• Experience with production-facing software development and strong debugging skills. This also requires demonstrating applied engineering skills through a shipped ML network or personal project.

• Understanding of 3D maths/geometry: Including multiple-view geometry and 3D mesh representations.

Nice-to-have

• Experience with Graphics and/or Game Engines

• Experience with Computer Vision

Benefits

• Discretionary bonus opportunity
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the country they reside in.

About the Program

The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.

What You'll Do

• ML Projects: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
• HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
• Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).

Who Should Apply

• Education: PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
• Professional Background: 1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
• Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.
• Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration.

Why Join the HFC?

• Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology.
• Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
• Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
• Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location. 

Application Process

1. Apply: We review applications on a rolling basis.
2. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
3. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.

See yourself at Twilio

Join the team as Twilio’s next Security Engineer, Security Automation on Twilio’s Information Security Team.

About the job

This position is needed to assist Twilio’s Information Security Team operate more efficiently by improving and automating our critical security workflows.

As a Software Engineer, Security Automation on this team, you will participate in all phases of the software development life cycle which includes requirements gathering with security teams, technical design, estimations, sprint planning, coding, testing, deployments and on-call support. You will own, operate and maintain automated workflows that support various security programs including but not limited to cloud security, product security, Governance, Risk & Compliance (GRC)  and enterprise security, employing Agile methodologies to continuously deliver value to our partners.

Responsibilities

In this role, you’ll:

• Develop and implement automated and AI-powered security solutions to protect Twilio's Cloud and Enterprise infrastructure, leveraging data orchestration frameworks and LLM-based approaches.
• Build workflows that integrate structured and unstructured data sources into orchestrated pipelines, enabling intelligent decision-making and risk reduction at scale.
• Design and prototype LLM-driven applications to automate security analysis, incident response, and governance tasks, while ensuring explainability and accuracy.
• Collaborate with cross-functional teams to identify security needs and deliver advanced AI-enabled solutions that address those needs effectively.
• Contribute significantly to defining our security automation and AI roadmap, balancing near-term and long-term business impact with technical feasibility and scalability.
• Own and maintain the operational health of automation and AI-driven systems, ensuring they continue to meet reliability and performance requirements (SLOs and KPIs).
• Support on-call operations for tools, pipelines, and AI models owned by the team.
• Document and share knowledge through clear technical documentation of processes, procedures, AI models, and orchestration systems.
• Stay up-to-date on emerging trends in security automation, data orchestration, and AI/LLMs—and apply them to Twilio’s security operations for continuous innovation.

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• Minimum of five (5) years of experience as a software engineer developing internal tools and automating workflows at scale
• Proficiency in Python (or another scripting language) for development, testing, and automation of security and infrastructure workflows
• Hands-on experience applying AI/ML models, including LLMs, to automate complex business or security processes and build intelligent solutions
• Solid understanding of software security principles, secure coding practices, and security automation
• Experience with data orchestration frameworks (e.g., Airflow, Dagster, Prefect) to manage and scale automation pipelines
• Familiarity with infrastructure-as-code (Terraform), CI/CD systems (BuildKite or similar), and container orchestration platforms (Kubernetes, Docker)
• Strong problem-solving, communication, and collaboration skills, with the ability to iterate quickly on feedback and work across security and engineering teams

Desired:

• Experience with Security Orchestration, Automation, and Response (SOAR) technologies and practices, with a focus on scaling automated incident response
• Proven ability to design and implement security automation frameworks that enable rapid delivery of reliable, reusable, and scalable automated solutions
• Strong interest in or hands-on experience with building and applying AI/ML models (including LLMs) to automate complex workflows in cybersecurity, compliance, or infrastructure operations
• Ability to bridge AI/automation capabilities with security strategy, driving adoption of next-generation solutions across cloud and enterprise environments
• Passion for continuous innovation in leveraging orchestration, automation, and AI to solve real-world security challenges

Location

This role will be remote, and based in the UK.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

See yourself at Twilio

Join the team as Twilio’s next Security Engineer, Security Automation on Twilio’s Information Security Team.

About the job

This position is needed to assist Twilio’s Information Security Team operate more efficiently by improving and automating our critical security workflows.

As a Software Engineer, Security Automation on this team, you will participate in all phases of the software development life cycle which includes requirements gathering with security teams, technical design, estimations, sprint planning, coding, testing, deployments and on-call support. You will own, operate and maintain automated workflows that support various security programs including but not limited to cloud security, product security, Governance, Risk & Compliance (GRC)  and enterprise security, employing Agile methodologies to continuously deliver value to our partners.

Responsibilities

In this role, you’ll:

• Develop and implement automated and AI-powered security solutions to protect Twilio's Cloud and Enterprise infrastructure, leveraging data orchestration frameworks and LLM-based approaches.
• Build workflows that integrate structured and unstructured data sources into orchestrated pipelines, enabling intelligent decision-making and risk reduction at scale.
• Design and prototype LLM-driven applications to automate security analysis, incident response, and governance tasks, while ensuring explainability and accuracy.
• Collaborate with cross-functional teams to identify security needs and deliver advanced AI-enabled solutions that address those needs effectively.
• Contribute significantly to defining our security automation and AI roadmap, balancing near-term and long-term business impact with technical feasibility and scalability.
• Own and maintain the operational health of automation and AI-driven systems, ensuring they continue to meet reliability and performance requirements (SLOs and KPIs).
• Support on-call operations for tools, pipelines, and AI models owned by the team.
• Document and share knowledge through clear technical documentation of processes, procedures, AI models, and orchestration systems.
• Stay up-to-date on emerging trends in security automation, data orchestration, and AI/LLMs—and apply them to Twilio’s security operations for continuous innovation.

Qualifications 

Not all applicants will have skills that match a job description exactly. Twilio values diverse experiences in other industries, and we encourage everyone who meets the required qualifications to apply. While having “desired” qualifications make for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

Required:

• Minimum of five (5) years of experience as a software engineer developing internal tools and automating workflows at scale
• Proficiency in Python (or another scripting language) for development, testing, and automation of security and infrastructure workflows
• Hands-on experience applying AI/ML models, including LLMs, to automate complex business or security processes and build intelligent solutions
• Solid understanding of software security principles, secure coding practices, and security automation
• Experience with data orchestration frameworks (e.g., Airflow, Dagster, Prefect) to manage and scale automation pipelines
• Familiarity with infrastructure-as-code (Terraform), CI/CD systems (BuildKite or similar), and container orchestration platforms (Kubernetes, Docker)
• Strong problem-solving, communication, and collaboration skills, with the ability to iterate quickly on feedback and work across security and engineering teams

Desired:

• Experience with Security Orchestration, Automation, and Response (SOAR) technologies and practices, with a focus on scaling automated incident response
• Proven ability to design and implement security automation frameworks that enable rapid delivery of reliable, reusable, and scalable automated solutions
• Strong interest in or hands-on experience with building and applying AI/ML models (including LLMs) to automate complex workflows in cybersecurity, compliance, or infrastructure operations
• Ability to bridge AI/automation capabilities with security strategy, driving adoption of next-generation solutions across cloud and enterprise environments
• Passion for continuous innovation in leveraging orchestration, automation, and AI to solve real-world security challenges

Location

This role will be remote, and based in Ireland.

Travel

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

There are many benefits to working at Twilio, including, in addition to competitive pay, things like generous time-off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

This is a remote role.

About Us
Reachdesk is the first truly end-to-end global SaaS gifting and swag platform, helping B2B companies create meaningful connections with prospects, customers, and employees, while driving measurable ROI.

We believe gifting is more than just a transaction: it’s about building genuine human connections that fuel business growth. Whether you’re engaging prospects, celebrating customers, or recognizing employees, our platform makes it easy to deliver personalized gifts, branded swag, and unforgettable event & brand experiences at scale through automated sourcing, storage, and global delivery.

We’re growing, and we’re currently looking for a Head of Business Systems & Operations to join us.

The Role

As the Head of Business Systems & Operations at Reachdesk, you will own and shape the systems and data architecture that underpin how the business operates. You will be responsible for connecting Finance, GTM, Product, and Customer teams through a single, trusted system landscape, ensuring data flows cleanly across Salesforce, NetSuite, Workato, and our BI layer. This is a high impact role where you will define how the business uses its systems, not just maintain them.

You will join at a critical stage as we complete our closed-loop architecture and transition ownership from product into the business. You will have full autonomy to design, govern, and evolve this ecosystem while embedding AI into core workflows and decision making. This role is particularly suited to someone who enjoys creating order from complexity: building a reliable, scalable foundation that the business trusts, enabling faster decisions, stronger financial control, and a step change in operational efficiency across Reachdesk.

Your Responsibilities

• Own the end-to-end systems and data architecture connecting Salesforce, NetSuite, Workato, the Reachdesk SaaS platform and the BI layer.
• Lead the transition of systems ownership into Business Operations and establish a clear operating model, governance framework, and roadmap that the business trusts and that can evolve as needs change, ensuring trusted, timely data flows across Finance, GTM, Product, and Customer teams.
• Lead from the front by setting technical direction from being in the systems alongside your team, not just reviewing their work. Define the go-forward BI architecture, ownership model, and roadmap.. 
• Complete and continuously evolve this architecture so every core process is underpinned by clean data and reliable automation.
• Establish an AI governance framework to embed AI into core workflows and decision-making, from forecasting and pipeline insights to customer health, billing, and operational automation, delivering measurable efficiency gains.
• Define and enforce master data management and integration standards across all systems.
• Partner closely with Finance, RevOps, Customer Operations, and Product to translate business priorities into scalable system solutions, balancing speed of delivery with long-term architectural integrity.
• Build, lead, and develop a small, high-performing team of systems and operations specialists, and manage external delivery partners where needed.
• Own vendor relationships, contracts, and roadmaps for our core SaaS stack, ensuring we get value, leverage, and influence over product direction, with a focus on finding efficiencies and cost savings.  
• Define and report on system health, data quality, and operational efficiency KPIs to the executive team and Board where relevant.

About You

You are a strategic systems leader with strong technical instincts and a pragmatic builder mentality. You see business systems as a competitive advantage, not a back-office function, and you are energized by the opportunity to shape the operating engine of a high-growth, PE-backed SaaS business. You understand the importance and value of data integrity and consistency, ensuring every department relies on the same core data and metrics. You are still in the system. You are as comfortable in a Salesforce flow, a NetSuite saved search, or a Workato recipe as you are in a strategy meeting. You believe leaders in this function lose their edge the moment they stop building, and you have no interest in becoming that person. You move comfortably between architecture decisions and detailed configuration, and you are equally at home in a conversation with the CFO, the CRO, or an engineer. You bring a hands-on operator mindset: you understand that great systems exist to make the business faster, sharper, and more accountable, and you measure your success by the decisions and outcomes they enable.

Must-have Qualifications

• 8+ years in Business Systems, RevOps, or BizTech leadership roles within B2B SaaS, with at least 3 years leading a function or team.
• Deep expertise across Salesforce and NetSuite, including a track record of designing and evolving the integration layer between them.
• Strong experience with iPaaS platforms (Workato strongly preferred) and modern BI tooling.
• Demonstrated ability to design and operate a closed-loop architecture, covering quote-to-cash, lead-to-revenue, and customer lifecycle, in a multi-entity, multi-currency environment.
• Demonstrably hands-on within the last 12 months and can speak in concrete detail about systems you have personally configured, automations you have built, or data models you have designed.
• Robust data governance and master data management discipline, with a clear point of view on ownership, lineage, and quality.
• Proven track record of leading complex, cross-functional systems programs end-to-end, on time and on budget.
• Excellent stakeholder management, particularly with Finance and GTM leadership, and the ability to translate technical decisions into commercial impact.
• People leadership experience with a coaching mindset, and the ability to build a small team that punches above its weight.

Preferred Qualifications

• Experience in a PE-backed, high-growth SaaS environment with tight financial control requirements.
• Familiarity with multi-stream revenue models (e.g. SaaS combined with services, marketplace, or fulfillment) and the revenue recognition complexity they bring.
• Experience embedding AI/ML or agentic automation into operational workflows, with named use cases, governance, adoption controls, and measurable business outcomes.
• NetSuite and/or Salesforce certifications.
• Experience transitioning systems ownership into a Business Operations function.
• Background working in a scaling SaaS business, comfortable operating across time zones and entities.

The Benefits

• Competitive salary with generous stock options
• Pension with employer contributions (NEST)
• Affordable Private Medical Insurance, including mental health support and fast access to care
• Flexible PTO that increases the longer you’re with us, plus extra flexibility for life’s unexpected moments
• A genuinely collaborative culture with innovative, fun, and ambitious people

Reachdesk believes that a diverse team helps us achieve our mission faster, and so we welcome applicants from all backgrounds.

Privacy Policy: We process personal information submitted as part of your application in accordance with the Reachdesk Candidate Privacy Notice. Please review Reachdesk’s Privacy Policy here: www.reachdesk.com/candidate-privacy-policy 

New data center development:

We give you the opportunity to work with cutting-edge technologies in data operations, cloud computing and infrastructure management. As global data center operations grow, there will be ample opportunities for career progression. Working in the data center directly impacts performance, customer satisfaction and efficiency, with the opportunity to contribute to new data center projects.You’ll collaborate with experts in AI data center development and operations, gaining insights from leaders in the field. This environment fosters innovation, and allows you to work on solutions that exceed industry standards in design and deployment.

The role 

We’re looking for an IT Infrastructure Engineer to support IT operations in multiple datacenters around the world. This is a position for a datacenter hardware expert working at the intersection of multiple technical domains

You’re welcome to work in our office in London, England. 

Your responsibilities will include: 

• Solve the most challenging firmware and hardware related issues with servers, involving in-depth knowledge of system architecture, network configurations and advanced troubleshooting

• Take charge of hardware problem management and develop new solutions

•  Act as a subject matter expert and point of escalation for team members

•  Collaborate with R&D to improve our hardware designs

• Create new processes and documentation for IT hardware team

• Improve support processes and training materials

• Travel to datacenters to participate in large scale hardware projects and collaborative events

We expect you to have: 

• Knowledge of datacenters, server and network equipment

• Deep knowledge of IT hardware and practical experience of troubleshooting

• Advanced skills working with the Unix operating system and command line

• Advanced network troubleshooting skills

• Experience with equipment monitoring, data analysis and presentation

• Proactiveness and sense of responsibility

• High proficiency in spoken and written English

It will be an added bonus if you have: 

• Technical certifications in relevant areas

• Skills in design and repairing electronic equipment

• Driving license type B

• Serverless AI has clear product-market fit with measurable activation and retention metrics improving quarter over quarter.
• Multi-node jobs and autoscaling endpoints are shipped and adopted by customers running production workloads.
• Cold start time is reduced from 1-3 minutes to under 60 seconds for common workloads through a combination of product and infrastructure improvements you drove.
• Developer experience (CLI, docs, error messages, onboarding flow) sets the standard that developers expect from a next-generation AI cloud.
• At least 3 product decisions you made are directly attributable to customer conversations or data analysis you conducted.

• Co-own the Serverless AI product roadmap — Jobs, Endpoints, and DevPods — taking primary ownership of specific product areas while collaborating closely with the other PM on shared priorities and cross-cutting decisions.
• Write detailed, technically precise PRDs that engineering teams can execute against. Our PRDs specify CLI syntax, API contracts, state machines, and billing models — not abstract feature descriptions.
• Make build/buy/defer decisions on capabilities like autoscaling, multi-node orchestration, HTTPS termination, secret injection, and health checking based on customer signal and strategic priorities.

• Understand the full workload lifecycle: container image pull → VM provisioning → GPU attachment → workload execution → cleanup — well enough to identify bottlenecks and propose solutions.
• Evaluate technical trade-offs in areas like container cold start optimization (image caching, snapshot restore, warm pools), GPU scheduling and bin-packing, and storage mount performance.
• Work directly with engineers on architecture decisions for distributed training support, endpoint autoscaling policies, and fault tolerance mechanisms.
• Stay current on the fast-moving serverless GPU infrastructure space — new inference frameworks (vLLM, TensorRT-LLM, SGLang), container runtimes, orchestration approaches — and translate trends into product direction.

• Run customer discovery and feedback sessions with ML engineers and platform teams at AI startups and enterprises. Turn qualitative insight into specific product actions.
• Analyze usage data, activation funnels, and churn patterns to identify where users get stuck and what features drive retention.
• Track market dynamics, emerging technologies, and industry trends to inform product strategy and ensure Nebius stays ahead of where the market is heading.
• Define and iterate on pricing, packaging, and tier strategy for Serverless AI.

• Own the technical content strategy: quickstart guides, tutorials, reference architectures, and example workloads that reduce time-to-first-job.
• Partner with marketing on developer-focused campaigns, webinars, and conference presence.
• Work with Solution Architects and Sales to qualify serverless-fit opportunities and support technical evaluations.

• You have built, shipped, and iterated on infrastructure or platform products used by developers or ML engineers. Not consumer apps. Not dashboards. Infrastructure.
• You understand containers at a practical level — Docker, image registries, container runtimes, resource limits, networking. You've debugged why a container won't start, why GPU isn't visible inside it, or why a mount isn't working.
• You have working knowledge of GPU computing for AI/ML: what GPU types exist and when to use them, how training and inference workloads differ in resource requirements, what vLLM / TensorRT-LLM / Triton are and why they matter.
• You can read a CLI reference and know if it's well-designed. You've shaped developer-facing APIs, CLIs, or SDKs.
• You have run real customer discovery — not surveys, but technical conversations with engineers where you learned something that changed your product direction.
• You have 3+ years of product management experience in cloud infrastructure, AI/ML platforms, or developer tools.

• Ability to whiteboard a workload lifecycle (submit → schedule → provision → execute → cleanup) and identify failure modes at each step.
• Understanding of autoscaling trade-offs: scale-to-zero vs. warm pools, scaling metrics (queue depth, latency, utilization), cold start implications.
• Familiarity with inference serving concepts: batching, model loading, quantization, KV-cache management, multi-model serving.
• Understanding of distributed training concepts: data parallelism, model parallelism, communication overhead, checkpointing.
• Ability to reason about pricing models: per-second vs. per-request vs. per-token, and how pricing interacts with product architecture.

• Experience at a serverless or GPU cloud company.
• Hands-on ML engineering background — you've trained models, deployed inference endpoints, or built ML pipelines yourself.
• Experience with Kubernetes for ML workloads (Kubeflow, KServe, Ray Serve) and understanding of why many ML teams want to avoid it.
• Prior experience building a product from early stage to scale in a fast-growing market.
• Background in systems engineering, distributed systems, or site reliability engineering.

• You are more comfortable in a terminal than in a slide deck.
• You form strong opinions based on data and direct customer signal, and you update them when evidence changes.
• You are energized by building at pace — small team, fast-evolving product, big opportunity.
• You care about developer experience at the level of error messages, CLI flag naming, and documentation quality.
• You'd rather ship a smaller thing that works perfectly than a bigger thing that's mediocre.

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. 

Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).  

Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. 

If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

The role

We are seeking a customer-obsessed Solutions Architect to lead technical engagement with Nebius customers across Europe. This role is focused on presales excellence, strong technical storytelling, and driving adoption of Nebius AI Cloud across a wide range of industry segments.

As a Solutions Architect, you will act as a trusted technical partner to customers, helping them understand, evaluate, and adopt Nebius for their AI/ML and high-performance computing workloads. You will combine deep technical expertise with strong communication skills to clearly articulate Nebius’ value proposition and differentiate our platform in a competitive market.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Own end-to-end technical presales engagements, from discovery through solution design, PoC execution, and production readiness
• Serve as a trusted technical advisor to customer stakeholders, including CTOs, Heads of AI/ML, and platform engineering teams
• Deliver compelling technical presentations, demos, and workshops that clearly communicate the value of Nebius across different customer segments
• Execute demos and PoCs to demonstrate performance, scalability, and cost efficiency of Nebius solutions
• Translate customer requirements into scalable, production-ready architectures and best practices
• Collaborate closely with Sales, Product, and Engineering to align customer needs with Nebius capabilities and roadmap
• Act as a technical advocate for customers internally, ensuring feedback is incorporated into product and go-to-market strategy
• Support regional go-to-market efforts, including events, meetups, webinars, and technical content creation
• Contribute to building repeatable technical playbooks and assets for the European market

We expect you to have:

• 2–5+ years of experience in technical roles such as Solutions Architect, Cloud Architect, Sales Engineer, or similar, with strong customer-facing exposure
• Proven experience in presales or customer-facing technical roles, including discovery, solution design, and PoC execution
• Strong ability to deliver technical pitches and clearly explain complex infrastructure and AI/ML concepts to both technical and business audiences
• Experience positioning cloud or infrastructure solutions and articulating value propositions in competitive environments
• Solid understanding of ML/AI workloads, including training and inference, and the underlying infrastructure requirements
• Experience with cloud platforms, Kubernetes, and distributed systems
• Hands-on experience with Infrastructure as Code (e.g., Terraform) and scripting/programming (Python preferred)
• Strong communication and storytelling skills, with the ability to adapt messaging across different customer segments
• Deep understanding of the European market, including customer expectations, buying behaviors, and local ecosystem
• Fluency in English plus another language preferred (both written and spoken), with the ability to engage confidently with local customers and stakeholders
• A highly customer-centric mindset, with the ability to balance technical depth and business value

It will be an added bonus if you have:

• Experience with GPU-accelerated workloads and AI infrastructure (NVIDIA ecosystem, CUDA, etc.)
• Hands-on experience with MLOps tools and frameworks (Kubeflow, MLflow, etc.)
• Familiarity with HPC environments and schedulers (e.g., Slurm)
• Experience contributing to regional go-to-market or developer/community initiatives

Token Factory is a part of  Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale. To deliver on that promise, we need an engineer who can make the platform behave flawlessly under extreme load and recover gracefully when the unexpected happens.

In this role you will own the reliability, performance, and observability of the entire inference stack. Your day starts with designing and refining telemetry pipelines — metrics, logs, and traces that turn hundreds of terabytes of signal into clear, actionable insight. From there you might tune Kubernetes autoscalers to squeeze more efficiency out of GPUs, craft Terraform modules that bake resilience into every new cluster, or harden our request-routing and retry logic so even transient failures go unnoticed by users. When incidents do arise, you’ll rely on the automation and runbooks you helped create to detect, isolate, and remediate problems in minutes, then drive the post-mortem culture that prevents recurrence. All of this effort points toward a single goal: scaling the platform smoothly while hitting aggressive cost and reliability targets.

Success in the role calls for deep fluency with Kubernetes, Prometheus, Grafana, Terraform, and the craft of infrastructure-as-code. You script comfortably in Python or Bash, understand the nuances of alert design and SLOs for high-throughput APIs, and have spent enough time in production to know how distributed back-ends fail in the real world. Experience shepherding GPU-heavy workloads — whether with vLLM, Triton, Ray, or another accelerator stack — will serve you well, as will a background in MLOps or model-hosting platforms. Above all, you care about building self-healing systems, thrive on debugging performance from kernel to application layer, and enjoy collaborating with software engineers to turn reliability into a feature users never have to think about.

If the idea of safeguarding the infrastructure that powers tomorrow’s multimodal AI energizes you, we’d love to hear your story.

The role 

The Data Engineering team is responsible for building and maintaining robust data infrastructure that powers analytics, and business intelligence across Nebius. We design and implement scalable data pipelines, optimize data storage and processing, and enable data-driven decision making across the organization. The team works closely with product teams and business stakeholders to ensure alignment with company goals.We are looking for a Data Engineer to design, build, and maintain our data infrastructure and pipelines. You will work on processing large-scale datasets, optimizing data workflows, and enabling analytics capabilities that support our rapidly growing cloud platform.

Your responsibilities: 

• Design, develop, and maintain scalable data pipelines.
• Build and optimize data infrastructure.
• Implement data quality monitoring and validation frameworks.
• Optimize data storage, processing, and query performance for large-scale datasets.
• Design and implement data models for analytics and reporting use cases.
• Develop tools and automation to improve data engineering workflows and productivity.
• Ensure data governance, security, and compliance standards are met.
• Participate in on-call rotation to support production data systems.

Must-haves: 

• 3+ years of experience in data engineering or related roles.
• Experience building and maintaining data pipelines using orchestration tools (e.g., Airflow, Prefect, Dagster).
• Strong proficiency in SQL and solid programming skills in Python.
• Experience with distributed data processing frameworks (e.g., Apache Spark, or similar).
• Knowledge of data modeling principles and best practices.
• Understanding of data architectures and storage systems.

Nice-to-haves: 

• Experience with real-time data streaming platforms.
• Familiarity with Infrastructure as Code tools (Terraform, etc).
• Experience with containerization (Docker) and Kubernetes.
• Knowledge of data governance and privacy frameworks (GDPR, SOC2).
• Knowledge of data quality and observability tools (Great Expectations, etc.).

We conduct coding interviews as part of the process.

The role

Token Factory is a part of Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference & fine-tuning platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to train & deploy at massive scale.

• Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency.

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation.                                                                                
• Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and reinforcement learning.

• Deep expertise in modern deep learning for language processing and generation

• Experience with training large models on multiple computational nodes

• Reasonable understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)

• Strong software engineering skills (we mostly use Python)

• Deep experience with modern deep learning frameworks (we use JAX)

• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

• Strong communication and leadership abilities

Nice to have:

• Previous experience working with language models or other similar NLP technologies.

• Familiarity with important ideas in LLM space, such as MHA, RoPE, ZeRO/FSDP, Flash Attention, quantization

• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.

• Strong engineering skills, including experience in developing large distributed systems or high-load web services.

• Open-source projects that showcase your engineering prowess

• Excellent command of the English language, alongside superior writing, articulation, and communication skills.

New data center development:

We give you the opportunity to work with cutting-edge technologies in data operations, cloud computing and infrastructure management. As global data center operations grow, there will be ample opportunities for career progression. Working in the data center directly impacts performance, customer satisfaction and efficiency, with the opportunity to contribute to new data center projects.You’ll collaborate with experts in AI data center development and operations, gaining insights from leaders in the field. This environment fosters innovation, and allows you to work on solutions that exceed industry standards in design and deployment.

The role

As a Field Network Engineer at Nebius, you will be responsible for providing IT support at remote locations and deploying data center IT infrastructure in new regions. Your primary focus will be managing projects and IT operations, primarily at our London, England data center, home to a major GPU cloud installation. This role requires frequent travel to support IT operations at other sites. 

You’re welcome to work in our location in London, England, UK. 

Your responsibilities will include: 

• Assist in the preparation and deployment of new infrastructure for upcoming launches.
• Troubleshoot and resolve hardware and network-related issues within our data centers.
• Manage and coordinate remote IT operations by collaborating with smart hands in co-located facilities. Be prepared to travel for on-site installations and technical support.
• Work closely with cross-functional teams and external contractors to ensure seamless project execution.
• Develop and maintain comprehensive technical documentation detailing service operations and best practices.

We expect you to have:

• 3+ years of hands-on experience in project planning and technical problem-solving.
• Strong understanding of network technologies, including data center, server and network equipment.
• Proficiency in IT hardware components, diagnostics and troubleshooting.
• Proactive, responsible, and goal-oriented mindset.
• Excellent written and verbal communication skills in English.
• Willingness to travel regularly for business trips.
• Relevant certifications (e.g., CCNA, CCNP)
• Valid Driving License 

It will be an added bonus of you have: 

• ITIL or/and PMI Certification

The role

Nebius seeks a Key Customers Solutions Architect to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include: 

• Serve as the primary technical point of contact, troubleshooting and resolving complex AI/ML.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5 - 10 + years in roles like Cloud Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

The role

We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work from the United Kingdom.

Your responsibilities will include: 

• Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
• Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
• Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
• Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
• Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: 

• 5+ years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
• Excellent communication skills
• Customer-centric mindset

It will be an added bonus if you have: 

• Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
• Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
• Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 

Nebius Managed Kubernetes (mk8s) mission is to grow the Nebius cloud platform by providing a Kubernetes-native way to run AI systems with high efficiency and low operational overhead.
With a single click, it provides a Kubernetes cluster on top of Nebius services for compute (VMs) and networking.
In 2026, the service is scaling 10× and is expected to manage customer workloads across tens of thousands of GPU servers in more than 10 data centers.

You will lead the mk8s Core team, one of three mk8s teams. The Core team owns the API, the core of the service control plane, cluster autoscaling, platform integrations, and running k8s add-ons.

At Nebius, team leads are hands-on. We expect you to be a senior or staff engineer now (or earlier in your career). You will start as an individual contributor to gain context, then take on managerial responsibilities.

In this position, you will be responsible to:

• Lead by example. Set the quality bar by spending a significant portion of your time on IC work: writing and reviewing code, leading projects, and participating in on-call rotation, incident mitigation, and post-incident analysis.
• Manage 4–8 mid-to-senior engineers. Provide context, coach, and give regular feedback.
• Maintain the technical vision for your area of responsibility.
• Collaborate with the Product Manager and Service Owner to shape product vision and plans.

Examples of outcomes you could drive as a Team Lead

• Optimize the service control plane to create and manage 20K GPU nodes in a single Kubernetes cluster, enabling a major contract for the company.
• Integrate cluster autoscaling approaches (e.g., Karpenter) to improve resource utilization and support seamless auto-upgrades.
• Provide a Kubernetes-native way to use local disks to reduce disk I/O bottlenecks for AI training and inference, improving efficiency.
• Deliver managed Layer 7 load balancers to reduce operational overhead for customers.

What you will bring to the table:

• 8+ years of professional software engineering or management experience
• Excellent knowledge of Golang, or you are ready to quickly switch to this programming language
• Expertise with
• Multi-month technical projects
• Tech leading engineers
• Owning multi-month technical projects.

It would be an added bonus if you had:

• Experience with Team management, Kubernetes administration, Developing Kubernetes controllers

The role

We’re looking for a Senior Backend Engineer to join our Storage Virtualization Team, building a distributed, fault-tolerant storage system for Nebius’ hyperscaler cloud.
You’ll work on high-performance block and filesystem storage that delivers sub-millisecond latency, millions of IOPS and terabytes per second of throughput, even in the face of hardware failures.

• Virtualization: virtio-blk and virtio-fs, QEMU and vhost-user, performance-critical I/O paths
• Networking: high-throughput VM-to-storage transport over TCP and RoCEv2 (RDMA)
• Storage systems: replication, consensus, self-healing, and data migration

• 6+ years of professional software engineering experience
• Strong knowledge of C++
• Solid understanding of algorithms and data structures
• Basic knowledge of operating system internals (I/O, memory, scheduling)
• Ability to write reliable, maintainable code and debug complex systems
• Team-oriented mindset and fluency in English

We conduct coding interviews as part of the process.

The role

We’re looking for a Backend Engineer to contribute to the development of our hyperscaler platform.

Your responsibilities will include:

Develop fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We expect you to have: 

• 5+ years of professional software engineering experience;
• Knowledge of C++ programming language;
• Knowledge of Python, Java, and Go is a plus;
• Ability to write reliable code and dig into complex problems;
• Teamwork-oriented approach;
• Fluency in English.

Nice to have:

Experience designing high-load and scaling services.

We conduct coding interviews as part of the process.

The Product

In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.

We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale.

The Role

We are looking for a Senior Software Engineer to work on the indexing and data processing layer of a novel search engine tailored for agentic AI consumption.

In this role, you will focus on building systems that ingest, process, and organise massive volumes of data into efficient, queryable structures. You will work primarily on offline and nearline pipelines, ensuring that data is fresh, complete, and efficiently accessible by downstream retrieval systems. You will operate in an environment where throughput, scalability, and correctness are critical — designing systems capable of handling tens of gigabytes per second across continuously evolving datasets.

In this position, your responsibility will be to

• Design, implement, and operate large-scale indexing systems and data pipelines that sit at the core of our search infrastructure
• Build ingestion workflows for internal and external data sources, including web-scale crawling and structured feeds
• Develop and optimise indexing strategies balancing performance, freshness, and resource efficiency
• Work on storage formats, compaction strategies, and update mechanisms to keep data accessible and current
• Ensure reliability and predictability of pipelines under high-throughput conditions
• Build well-tested components with clear responsibilities and interaction contracts, while remaining flexible as the system evolves
• Define and implement observability primitives, including structured logs, metrics, and data quality signals across offline and nearline pipelines
• Monitor throughput, resource usage, and cost, and drive optimisations when business needs require it
• Collaborate with runtime and ML teams to ensure indexing outputs meet retrieval and ranking requirements
• Enable safe experimentation on indexing strategies and data processing logic through controlled rollouts and clearly defined quality signals

You may be a good fit if you:

• Have 5+ years of experience building production backend or data systems
• Have strong hands-on experience with Go in real-world, high-load services (experience with other systems languages such as C++ or Rust is a plus)
• Have worked on systems at significant scale — such as 10k+ RPS or 10+ GiB/sec throughput
• Have experience building or operating databases, data planes, or large-scale data pipelines
• Understand distributed systems fundamentals, including fault tolerance, failure modes, and horizontal scalability
• Have operated your own systems in production: handled incidents, made real-world tradeoffs, and understand what running data infrastructure at scale truly involves
• Think in terms of systems and data flows rather than isolated components, reasoning end-to-end about how data moves through the stack
• Can make pragmatic decisions under pressure without compromising long-term system health
• Collaborate effectively across infrastructure, ML, and product teams, communicating clearly in cross-functional settings

Strong candidates may also have experience with:

• Distributed data processing frameworks such as Spark, Flink, MapReduce, or Beam
• Content systems including web crawling, scraping, proxying, or anti-bot infrastructure
• Ad tech, social networks, or other large-scale content platforms
• DBMS internals (open source or SaaS) and cloud infrastructure
• Open-source contributions or active involvement in the engineering community
• Competitive programming or CTF participation (ICPC, IOI, or similar)
• SHAD or similar advanced technical programmes
• Conference talks or technical publications

We conduct coding interviews as part of the process.

Nebius is looking for a Senior Technical Recruiter to strengthen our Talent Acquisition team and help us attract top technical talent. In this role, your primary focus will be on active sourcing and building strong pipelines of backend engineers, system engineers, and technology experts to support the company’s continuous growth.

Remote working, Based in the UK (London) OR Netherlands, working Hybrid from Amsterdam.

Your responsibilities will include:

• Technical Talent Sourcing: Proactively identify and engage engineers and other tech specialists through diverse channels (LinkedIn, GitHub, Boolean Search, professional communities, conferences, forums, networking, employee referrals).

• Pipeline Development: Build, maintain, and continuously refresh a pool of qualified engineers and developers for current and future hiring needs; provide funnel statistics to Hiring Managers (e.g., number of applicants, time to hire, etc.).

• Candidate Engagement: Craft personalized outreach and communication to spark interest and showcase opportunities at Nebius. Engage in pre-onboarding activities and contribute to HR projects.

• Screening: Conduct resume reviews and initial calls to assess candidates’ technical background, experience, and motivation.

• Collaboration with Hiring Managers: Partner with engineering leaders to deeply understand role requirements and design effective sourcing strategies.

• Market Research & Insights: Stay on top of industry trends, tech community activity, and competitor hiring practices. Identify the best companies to target for top-tier technical talent.

We expect you to have:

• 4+ years of experience in technical recruitment, specializing in Backend/General Tech such as (but not limited too): Software Engineers, Python Engineers, Platform Engineers, Cloud Platform Engineer, Site Reliability and Infrastructure Engineers, DevOps, Systems Engineers and Data Platform Engineers.

• Strong sourcing expertise and familiarity with tech talent pools, platforms, and communities.

• Deep understanding of tech subject areas, developers’ roles, technologies, and motivations, plus insight into which companies are the best sources of top candidates.

• Ability to manage multiple priorities and work in a fast-paced environment.

• Excellent follow-through, organizational, presentation, and communication skills (both written and verbal).

• Creative problem-solving skills with the ability to adapt quickly.

The team

Customer experience at Nebius GPU AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are seeking a highly skilled and customer-focused leader to join our team as a Cloud Solutions Architect Lead. As a team leader, you will play a pivotal role in customer success across EU region, both managing the efforts of Cloud Solutions Architects team (technical and process excellence, talent development) and building processes alongside your stakeholders. Player-coach mentality and proven track record of managing high expertise teams is a must. 

You’re welcome to work from our office in Amsterdam or remotely from any EU country.

Your responsibilities will include: 

• Lead and mentor a team of Solutions Architects, fostering a culture of technical excellence, customer empathy, and collaborative execution.
• Oversee and participate in technical engagements including PoCs, workshops, architecture reviews, and trainings.
• Drive consistency and quality across infrastructure design, IaC practices, technical documentation, and customer enablement content.
• Collaborate closely with Product and Development teams, representing customer needs and helping shape the roadmap.
• Guide customers in optimizing ML/AI/HPC pipelines for performance, scalability, and cost-efficiency on Nebius  cloud infrastructure.
• Build visibility and ownership culture amongst Solutions Architects.

We expect you to have: 

• 5+ years of experience in a technical role (Solutions Architect, DevOps Engineer, ML Engineer, or similar) with a focus on cloud-native systems and distributed computing.
• 2+ years of experience leading or mentoring customer facing engineering teams.
• Deep hands-on experience with Infrastructure as Code (Terraform, Ansible), Kubernetes, and cloud automation.
• Strong communication and stakeholder management skills across both technical and non-technical audiences.
• Passion for developing scalable, reliable cloud architectures and driving customer success.

It will be an added bonus if you have: 

• Experience with HPC or ML orchestration frameworks (e.g., Slurm, Kubeflow, Ray).
• Strong coding skills in Python and experience with GPU computing environments for ML/AI workloads.
• Proficient in GPU stack components (e.g., CUDA, cuDNN) and cloud-native patterns for ML training/inference.
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX).
• Understanding of cloud-based ML tools and offerings from NVIDIA, AWS, Azure, or Google Cloud.
• Experience participating in or leading technical contributions to conferences or open-source communities. 

The role

We are looking for a Customer Engineer to support key and strategic Nebius GPU Cloud services customers. In this role, you will be a trusted technical advisor, helping clients design, deploy, and scale AI solutions while managing large-scale GPU workloads involving hundreds to thousands of GPUs. You will also collaborate with sales and product teams to drive growth and enhance customer satisfaction.

You’re welcome to work remotely from Europe.

Your responsibilities will include:

• Serve as the primary technical point of contact for troubleshooting and resolving complex AI/ML issues.
• Guide customers in optimizing GPU performance for ML training and inference workloads, ensuring seamless integration and scalability.
• Partner with the sales team to identify new opportunities, promote the latest products, and deliver technical presentations.
• Act as a bridge to product teams, providing customer feedback, relaying feature requests, and ensuring alignment with customer requirements.
• Engage with internal and external stakeholders, negotiate solutions, and effectively drive alignment to address customer challenges.

We expect you to have:

• Experience: 5+ years in roles like Solutions Architect, Technical Account Manager, or Customer Engineer, with hands-on experience in cloud services and AI/ML workloads.
• Proficiency in Infrastructure as Code (IaC) tools like Terraform and Ansible.
• Experience with Kubernetes and Python programming.
• Solid understanding of GPU computing, including ML training, inference workloads, and GPU stacks (e.g., CUDA, OpenCL).
• Customer-centric approach with a proven ability to build trust and foster long-term relationships.
• Strong ability to explain technical concepts to technical and non-technical audiences.

It will be an added bonus if you have:

• Hands-on experience with HPC/ML orchestration frameworks (e.g., Slurm, Kubeflow).
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with ML tools from NVIDIA, AWS, Azure, and Google Cloud providers.
• Strong project management skills, with the ability to prioritize tasks and deliver on deadlines.
• Proven experience mentoring technical teams and driving team growth.
• Expertise in stakeholder negotiation to support problem resolution and ensure seamless collaboration.

The role

Token Factory is a part of Nebius Cloud, one of the world's largest GPU clouds, running tens of thousands of GPUs. We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits. Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.

Some directions we are currently working on, and which you can be a part of:

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
• Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
• Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and transformer architecture.
• Experience profiling GPU workloads using Nsight, PyTorch profiler, or similar tools
• Understanding of GPU memory hierarchy and compute/memory tradeoffs
• Familiarity with important ideas in LLM space, such as MHA, RoPE, KV-cache, Flash Attention, and quantisation
•  Understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)
•  Strong software engineering skills (we mostly use Python)
• Deep experience with modern deep learning frameworks
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing
• Strong communication and leadership abilities

Nice to have:

• Experience working with open-source inference engines (vLLM, SGLang, TensorRT-LLM), including contributions
• Experience with kernel languages or DSLs such as Triton, Cute, CUTLASS, CUDA
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess
•  Excellent command of the English language, alongside superior writing, articulation, and communication skills.

The role

This role is for Nebius AI R&D, a team focused on applied research in AI. Examples of applied research that we have recently published include:

• applying reinforcement learning for agent training in long-context multi-turn scenarios
• dramatically scaling task data collection to power reinforcement learning for SWE agents
• building a decontaminated evaluation for SWE agents that is regularly updated
• investigating how test-time guided search can be used to build more powerful agents

The results often lead to collaboration with adjacent teams where our research findings are applied in practice.

We are currently looking for senior- and staff-level ML engineers to work on research in areas such as:

• Guided search and reinforcement learning for agentic systems
• Reinforcement learning for reasoning models
• Web-scale problem collection for training agents
• Efficient model distillation

Some examples of what your responsibilities might include are:

• Conducting experiments to figure out efficient ways to train a large language model on traces of interactions with various environments
• Exploring methods of guided generation and search in the trajectory space
• Coming up with ways to mine relevant data at web scale and figuring out efficient ways to use this data in model post-training
• Conducting experiments with different reinforcement learning configurations in verifiable domains
• Exploring methods to train AI agents on tasks with non-verifiable reward signals

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and reinforcement learning
• Deep expertise in modern deep learning for language processing and generation
• Substantial experience with training large models on multiple computational nodes
• Strong software engineering skills (we mostly use python)
• Deep experience with modern deep learning frameworks (we use jax)
• Strong communication and leadership abilities
• Experience designing, executing, and analyzing machine learning experiments with proper statistical rigor
• Ability to formulate research questions, design experiments to test hypotheses, and draw meaningful conclusions from results
• Ability to document research findings clearly and contribute to technical publications or report

Nice to have:

• Experience with deep reinforcement learning for LLMs, including techniques such as reward modeling, DPO, PPO etc
• Familiarity with important ideas in LLM space, such as RoPE, ZeRO/FSDP, Flash Attention, quantization
• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field Master’s or PhD preferred
• Track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment
• Experience in engineering complex systems, such as large distributed data processing systems or high-load web services
• Open-source projects that showcase your engineering prowess
• Excellent command of the English language, alongside superior writing, articulation, and communication skills
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

The role

We’re looking for a Software Engineer with strong C++ expertise to join the team building and operating Nebius Data Platform — a distributed storage and a processing platform that acts as the company’s “source of truth” and the backbone of many internal (and some external) products.

Nebius Data Platform is a single multi-tenant ecosystem based on YTsaurus — instead of running separate HDFS/Kafka/HBase-style systems, we provide storage, compute, and analytics capabilities inside one platform.

Built on top of the open-source YTsaurus ecosystem, we run and extend our own Nebius distribution and develop significant in-house functionality (core and platform-level). We can design, implement, and roll out features end-to-end on our clusters without waiting for upstream approvals and contribute upstream when it makes sense.

At scale today, this includes~500 servers, ~20k CPU cores and ~10 PB of compressed data in our largest production cluster, supporting workloads ranging from business-critical pipelines and financial transactions to large-scale ML/LLM training datasets and compute.

What’s inside the platform

You’ll work on a system that includes (and ties together):

• Distributed Storage (Cypress): transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations.
• Compute & ETL: a cluster-wide job scheduler (tens of thousands of cores), MapReduce, YQL for SQL-like data processing, and SPYT (Spark over YTsaurus) for modern data engineering.
• Interactive analytics (CHYT): ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place.
• Dynamic Tables: low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores.
• Orchestracto: workflow orchestration deeply integrated with the platform (Airflow-like, but platform-native).

What you’ll do

We’re looking for engineers who combine strong systems skills with product sense: understanding who uses the platform, why certain capabilities matter, and making pragmatic trade-offs to maximize impact. On our team, engineering work is expected to be connected to real users and outcomes — you’ll regularly align with internal stakeholders, clarify requirements, and help drive prioritization.

In this role, you will:

• Design and implement new functionality in YTsaurus core (C++) with production reliability in mind.
• Build and evolve platform-level capabilities: platform architecture and operating model—multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases.
• Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation.
• Own production quality: incident response / on-call rotation, root cause analysis, and turning learnings into durable fixes.

Example projects

• Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10–100x cluster growth.
• Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection.
• Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows.
• Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability.
• Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths.

Tech stack

• Core: modern C++ (C++20, async + multithreaded primitives)
• Services & tooling: Go and Python (microservices, utilities, integration tests)

What we expect

• 5+ years of software engineering experience.
• Strong C++ skills (you’ll write core code).
• Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them).
• Experience developing and/or operating high-load, distributed services.
• Production mindset: ability to use SSH, read logs/metrics/traces, and debug distributed systems behavior.
• Solid CS fundamentals: algorithms, data structures, concurrency basics.

Nice to have

• Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems).
• Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering.
• Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs).

We conduct coding interviews as part of the process.

The Product

In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.

We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale.

The Role

We are looking for a Senior Software Engineer to work on the runtime systems of a novel search engine tailored for agentic AI consumption.

In this role, you will focus on building low-latency, high-throughput systems that serve search queries in real time. You will work on the critical path of user-facing requests, where performance, predictability, and efficiency directly impact product quality. You will design and operate systems that handle thousands of requests per second under strict latency budgets, optimising every layer from request handling to data access and response assembly.

In this position, your responsibility will be to

• Design, implement, and operate core runtime services for serving search queries at scale
• Build and optimise request flows, including query processing, retrieval orchestration, and response assembly under strict latency budgets
• Develop systems that maintain performance and predictability under high load
• Optimise CPU, memory, and data access patterns in performance-critical paths
• Ensure reliability, observability, and predictability across production services
• Build well-tested systems with clear responsibilities and interaction contracts, while remaining flexible as architecture evolves
• Define and implement observability primitives, including structured logs, metrics, traces, and latency breakdowns
• Monitor throughput, latency, and resource usage, and drive improvements in performance and cost efficiency
• Collaborate with indexing and ML teams to integrate retrieval and ranking components, keeping ML logic decoupled from core system internals
• Support experimentation and iteration through controlled rollouts and rigorous benchmarking

You may be a good fit if you:

• Have 5+ years of experience as a software engineer working on production backend systems
• Have strong hands-on expertise in C++ or Rust in real-world, high-load services
• Have built and operated high-load, low-latency user-facing systems handling thousands of RPS under strict latency constraints
• Understand performance at a systems level — CPU, memory, networking, and data access
• Have operated your own code in production: deployed it, debugged incidents, and rolled back changes when necessary
• Think end-to-end about request flows rather than staying within isolated components
• Can balance correctness, latency, and development velocity, making pragmatic tradeoffs when scope or time requires
• Collaborate effectively across engineering, ML, and product teams, communicating clearly in cross-functional settings

Strong candidates may also have experience with:

• DBMS internals (open source or SaaS) and cloud infrastructure
• High-load web applications or large-scale APIs
• Performance-critical systems such as trading platforms or real-time data pipelines
• Low-level performance tuning and hardware-level optimisation
• Open-source contributions or active involvement in the engineering community
• Competitive programming or CTF participation
• SHAD or similar advanced technical programmes
• Conference talks or technical publications

We conduct coding interviews as part of the process.

About the role:

Token Factory is a part of  Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale.

Responsibilities:

• Develop and optimize low-level kernels and runtime components for AI inference 

• Improve performance of inference engines GPU platforms 

• Profile and debug system-level and hardware-level performance issues 

• Integrate support for new hardware architectures (Hopper, Blackwell, Rubin) 

• Collaborate with ML and backend teams to optimize end-to-end execution 

Required Qualifications:

• Strong proficiency in C++, OR expertise in GPU programming with a focus on low-level high-performance coding and memory management 

• Experience in GPU programming or systems-level software development, e.g. operating system internals, kernel modules, or device drivers 

• Hands-on experience with profiling and debugging tools to identify performance issues on both CPUs and GPUs, and the ability to optimize code based on those findings. 

• Solid understanding of CPU/GPU architecture and memory hierarchy 

Preferred Qualifications: 

• Experience with GPU computing programming: CUDA, ROCm, CUTLASS, Cute, ThunderKittens, Triton, Pallas, Mosaic GPU 

• Familiarity with ML inference runtimes (e.g. TensorRT, TVM) 

• Knowledge of Linux internals, drivers, or compiler toolchains 

• Experience with tools like perf, VTune, Nsight, or ROCm profiler 

• Familiarity with popular inference engines (e.g. such as vLLM, sglang, TGI) 

We conduct coding interviews as part of the process.

We are seeking a Senior Applied ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time. This is a high-impact role working on a production system used 24x7, tackling challenges comparable to large-scale web search.

Your responsibilities:

• Design, train, and deploy ML models for retrieval, reranking, and search relevance in production
• Build and optimise embedding-based indexing and large-scale retrieval systems
• Develop models supporting crawling, data selection, and content understanding
• Define and improve quality metrics for agent-native search and build evaluation pipelines
• Work on systems operating at very large scale, including high-throughput query workloads
• Collaborate closely with engineering teams to integrate ML models into production services
• Analyse performance trade-offs across latency, quality, and cost
• Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems
• Contribute to product and architectural decisions in a fast-moving environment

Must-haves:

• 5+ years of experience in software engineering or applied machine learning
• Strong programming skills in Python, Go, or C++
• Proven experience deploying ML models in production systems
• Hands-on experience with retrieval, ranking, recommendation, or similar ML problems
• Strong understanding of machine learning and modern deep learning techniques
• Experience working with large-scale data systems and high-throughput environments
• Ability to design evaluation frameworks and define meaningful model metrics
• Product-oriented mindset with a focus on impact and iteration
• Strong problem-solving skills and ability to work in a distributed team

Nice-to-haves:

• Experience with search systems or large-scale information retrieval
• Familiarity with embeddings, transformers, and modern NLP systems
• Experience working on LLM-powered or agent-based systems
• Contributions to open-source projects, technical publications, or conference talks
• Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability

We conduct coding interviews as part of the process.

The role

This role is for Nebius AI R&D, a team focused on applied research and the development of AI-heavy products. Examples of applied research that we have recently published include:

• investigating how test-time guided search can be used to build more powerful agents;
• dramatically scaling task data collection to power reinforcement learning for SWE agents;
• maximizing efficiency of LLM training on agentic trajectories.

One example of an AI product that we are deeply involved in is Nebius Token Factory — an inference and fine-tuning platform for AI models.

This role will require expertise in distributed systems to build large-scale LLM training platform.

Your responsibilities will include: 

• Designing and developing LLM training platform.
• Maintaining our ML infrastructure, ensuring optimal performance, scalability and reliability.
• Improving job scheduling strategies to minimize resource fragmentation. 

We expect you to have:

• 5+ years of professional software development experience.
• Strong software engineering skills (we mostly use Python and Go).
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing.
• Experience with developing web services.
• A commitment to maintaining extreme rigor in all job-related activities.

Nice to have:

• Previous experience working with language models or other similar NLP technologies.
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess.

Role & Team

We’re looking for a Director of Platform & Infrastructure to own and evolve our core engineering foundations. Reporting to our VP of Product Engineering, this role will lead SRE, MLOps, and Platform teams with a mandate to create leverage across the entire organization.

As a scaling startup, we’re evolving from early-stage infrastructure to a more mature, reliable platform that can support rapid product development and growing customer demand. This role is critical in helping us make that transition — building systems, standards, and teams that enable speed today while laying the foundation for long-term scale.

Partnering closely with product, data, and application engineering teams, you will set the technical vision, define best practices, and ensure our infrastructure enables teams to move fast with confidence.

This is a highly cross-functional leadership role for someone who combines deep technical judgment with a systems mindset, strong people leadership, and a passion for building platforms that empower others.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do 

• Own the platform strategy across Platform, MLOps, and SRE, aligning it with company and product goals
• Grow senior ICs (and eventually manages) across multiple teams, fostering strong technical leadership and healthy team cultures
• Define and evolve our platform vision, including developer experience, internal tooling, CI/CD, infrastructure, observability, and reliability standards
• Oversee MLOps systems that support model development, training, deployment, monitoring, and governance in production
• Partner cross-functionally with Product, ML, Data, Security, and Compliance to ensure the platform meets current and future needs
• Balance speed and stability, making thoughtful tradeoffs between innovation, cost, reliability, and operational excellence
• Set metrics and accountability for platform performance, reliability, and developer productivity

Skills & Experience

• 10+ years experience leading platform, infrastructure, or reliability teams in a scaling startup environment, including navigating ambiguity, rapid growth, and the transition from early-stage systems to more mature, repeatable platforms
• Strong understanding of cloud-native infrastructure (GCP strongly preferred), Kubernetes, CI/CD, and modern DevOps practices
• Experience supporting machine learning systems in production, including model deployment, monitoring, and lifecycle management
• A track record of building reliable, scalable systems used by fast-moving product teams
• Excellent people leadership skills — you know how to coach managers, grow talent, and build inclusive, high-performing teams
• Strong communication skills and the ability to influence across org boundaries
• Experience in data- or ML-heavy products

Nice To Have

• Experience with geospatial data, image processing or mapping technology 

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits.  
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

Why Cast AI?

Cast AI is an automation platform that operates cloud-native and AI infrastructure at scale. By embedding autonomous decision-making directly into Kubernetes and cloud environments, Cast AI continuously optimizes performance, reliability, and efficiency in production.
The old way doesn't work. As Kubernetes and AI environments grow, manual decisions don’t. Cast AI replaces tickets, alerts, and manual tuning with continuous automation that adapts infrastructure as conditions change. Efficiency and cost savings follow naturally from that automation.
Over 2,100 companies already rely on Cast AI, including Akamai, BMW, Cisco, FICO, HuggingFace, NielsenIQ, Swisscom, and TGS.

Global team, diverse perspectives

We're headquartered in Miami, but our impact is international. We take a global and intentional approach to diversity. Today, Cast AI operates across 34 countries spanning Europe, North America, Latin America, and APAC, bringing a wide range of perspectives into how we build and lead.

Unicorn momentum

In January 2026, we achieved unicorn status with a strategic investment from Pacific Alliance Ventures, the corporate venture arm of Shinsegae Group (a $50+ billion Korean conglomerate). Our valuation now exceeds $1 billion, and we're just getting started.

Join us as we build the future of autonomous infrastructure.

About the role

Throughput. Latency. KV cache utilization.

Move those three numbers in the right direction, and two things happen: customers get faster, cheaper inference, and our margins improve. That's the entire thesis of this role. Every kernel you tune, every quantization scheme you ship, every scheduler tweak you land shows up directly in a customer's p99 and on our P&L.
This is a high-impact seat. It is also a high-autonomy seat as you'll be given the room to lead the technical direction of inference optimization at Kimchi, not execute someone else's roadmap.

The problem: running LLMs in production is a moving target. The "right" model and serving configuration for a workload depend on traffic shape, sequence-length distribution, batch dynamics, GPU SKU, memory bandwidth, quantization tolerance, and a dozen other variables that shift week to week. Most teams pick a model once, over-provision GPUs, and absorb the cost. Kimchi is the system that makes that decision automatically - continuously matching workloads to the most cost-efficient, best-performing LLM and serving configuration on a customer's infrastructure. We're building the optimization layer between the model and the hardware, and we need engineers who understand both sides deeply.

Stack

Python; vLLM; SGLang; TensorRT-LLM; PyTorch; CUDA-adjacent tooling; Kubernetes; gRP; ClickHouse; PostgreSQL; GCP Pub/Sub; AWS / GCP / Azure; GitLab CI; ArgoCD; Prometheus; Grafana; Loki; Tempo.

Requirements:

• 5+ years building real ML systems, with a portfolio that shows depth in inference or training infrastructure (not just model training notebooks).
• Strong Python - production services, not scripts.
• Hands-on experience with at least one of vLLM, SGLang, or TensorRT-LLM, and a working mental model of why an inference engine performs the way it does on a given GPU.
• Fluency with quantization tradeoffs - you've measured quality regressions, not just compression ratios.
• Comfort with distributed systems: collective communication, sharding strategies, and the practical failure modes of multi-GPU and multi-node setups.
• A bias toward measurement. You instrument before you optimize, and you can tell the difference between a real win and a benchmark artifact.
• Self-direction. This role comes with a wide mandate; you should be excited by that, not unsettled by it.

Responsibilities:

• Push throughput. Continuous batching, speculative decoding, chunked prefill, kernel-level tuning across vLLM, SGLang, and TensorRT-LLM. Find the ceiling on each GPU SKU, then raise it.
• Cut latency. Attack TTFT and TPOT separately. Profile, identify the actual bottleneck (compute, memory bandwidth, scheduling, networking), and fix it - not the bottleneck you assumed.
• Get more out of the KV cache. Paged attention, prefix caching, eviction policies, cache reuse across requests, quantized KV. This is where a lot of the unrealized throughput lives, and it's an area you'll own.
• Quantize without regressing quality. INT8, INT4, FP8 across weights, activations, and KV. Empirical work: measure quality on real workloads, not just perplexity benchmarks.
• Shrink cold starts and memory footprint. Faster init, smarter weight loading, tighter memory accounting - the difference between a model that scales and one that doesn't.
• Scale across nodes. Distributed inference topologies, network-aware placement, checkpointing strategies that don't bottleneck on storage or interconnect.
• Set the technical direction. Decide what we benchmark, what we adopt, and what we build ourselves. Bring the team along with strong writeups and reproducible experiments.

What’s in it for you?

• Competitive salary (depending on the level of experience).
• Enjoy a flexible, remote-first global environment.
• Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology
• Equity options.
• Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.
• Spend 10% of your work time on personal projects or self-improvement. 
• Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills.
• Annual hackathon to spark new ideas and strengthen team bonds.
• Team-building budget and company events to connect with your colleagues.
• Equipment budget to ensure you have everything you need.
• Extra days off to help maintain a healthy work-life balance.

Hiring process

• Screening call with Recruiter
• Hiring Manager interview
• Technical interview (system design)
• Live coding
• Culture Check interview with an executive

As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.
Please note that Cast AI does not provide any form of visa sponsorship/work permit.

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