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

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.

About the role

The Roku’s software automation and tools team has an excellent opportunity for a Senior Software Engineer with strong experience in building automation framework and tools for SW 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.

You will work cross-functionally with various engineering teams, using your finest automation expertise to help both FW developers and QA to create and deliver highest quality product that help in provide valuable end-user feedback to improve customer’s experience.  This position requires python expertise with strong experience of 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 keep up 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 consumer electronics space. As an engineer on the team you will require 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'll be doing

• Support and maintain existing automation tools and technology
• 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, product behavior
• Mentor less experienced engineers and driving automation development
• Assist in monitoring and maintenance of critical systems

We're excited if you have

• 5+ years of hands-on experience with automation systems
• 5+ years of programming experience, preferably with Python
• Bachelor’s degree in Computer Science or related
• Proficient in linux, Python based test automation frameworks and tools using REST APIs
• Hands on experience in development/integration of E2E test automation framework and tools for embedded software devices
• Experienced in developing and maintaining web based tools using Javascript, React
• Proficiency with DevOps, continuous integration tools (Jenkins, Gitlab CI, Teamcity, 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, playwright for UI testing
• Experience of developing web applications using Flask, FastAPI, Django, Nginx
• Experience and knowledge of using generative AI
• 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 being flexible/adaptable to change
• Comfortable and experienced working with cross-functional peers and internal stakeholders across European and US timezones
• Excellent communication and collaborative skills
• Experience with retail Consumer Electronic (CE) devices, ideally in the Over The Top (OTT) streaming domain
• Previous experience with Non-Functional Testing (Performance Testing, Stress Testing)
• Knowledge of network technologies and libraries such as TCP/IP and HTTP
• Previous experience and knowledge of image processing and inferencing, creating computer vision capabilities for visual testing

#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 Ads Analytics team plays a critical role in Roku’s Advertising organization, leading measurement and analytics initiatives that power decision-making across the advertising ecosystem. We develop and manage products that deliver actionable insights for advertisers while meeting the operational and analytical needs of internal business teams. 

We work closely with Product Managers, Ad Sales, Ad Operations, Data Science, and multiple other software teams within the Advertising Engineering organization to deliver high-impact solutions.  

Looking ahead, we are exploring AI-driven measurement capabilities to further enhance the effectiveness of advertising campaigns and strengthen internal analytics. 

About the Role 

We are seeking a high skilled Senior Software Engineer with deep expertise in API Development using Spring Boot while also possessing knowledge of Apache Spark-based Big Data pipelines using 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. 

You will communicate and collaborate heavily with both business and engineering to ensure high quality standards and overall project delivery success. In this role, you will collaborate with cross-functional teams to architect and manage robust, production-grade data products that power critical analytics and measurement capabilities. You will work with technologies such as Apache Spark, Apache Airflow, Trino, Druid, Spring Boot, StarRocks, and Looker to deliver reliable, high-performance solutions. 

The ideal candidate is a proactive, self-motivated professional with a strong track record in building applications and services with 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 analytics workflows. 

• Write clean, maintainable, and efficient code and tests, 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 and analytics solutions using Druid, Trino, and StarRocks for large-scale datasets. 

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

Collaboration & Mentorship 

• Partner with data scientists, 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: Apache Druid, StarRocks, and Trino. 

• Strong understanding of SOLID principles and distributed systems architecture. 

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

• Strong programming skills in Java, Python, or Scala.

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

• Expertise in data modeling, schema design, and data visualization tools.

• Experience building highly scalable, low-latency, APIs.

• Exceptional problem-solving abilities and the capacity to work both independently and collaboratively as needed. 

• Exceptional 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 campaign measurement. (preferred)

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

• 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). 

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 

We are building a next-generation observability and cloud platform that is high-performance, cost-efficient, secure, and scalable across multi-region, multi-cloud clusters. You will lead the architecture and evolution of Roku’s observability and cloud infrastructure stack. This includes metrics, logs, traces, telemetry pipelines, service mesh, developer experience, and reliability of systems that power thousands of services and millions of devices. 

You will drive a vision where developers gain deep visibility with minimal overhead, onboarding is seamless, and insights are available in real time. Your work will directly help Roku scale efficiently while maintaining reliability, cost control, and performance. 

What You’ll Be Doing 

• Architect and lead Roku’s observability platform across metrics, logs, and traces; evolve data pipelines and storage layers optimized for high throughput, performance, and cost at Roku scale (TSDBs, Parquet, distributed processing). 

• Extend and harden open‑source observability systems; overhaul core components (e.g., storage layers, query paths) to improve performance, reliability, and usability at scale. 

• Implement features such as pre‑aggregation, down-sampling, and sampling to reduce load and accelerate queries across the platform. 

• Collaborate across platform, SRE, and product teams to migrate hundreds of workloads to our common platform; augment and automate CI/CD flows and onboarding. 

• Integrate security into infrastructure and platform services; ensure robust multi‑tenant, multi‑cluster, and multi‑cloud designs. 

• Contribute improvements back to open source and CNCF‑aligned projects; shape standards adoption (OpenTelemetry, OpenMetrics) across the company. 

• Mentor engineers; establish best practices for reliability, efficiency, and cost management across service mesh and observability domains. 

What You'll have  

• Extensive experience with  software engineering with a track record of architecting distributed systems or platforms at scale. 

• Strong hands‑on experience in Golang and one scripting language (e.g., Python or Shell). 

• Experience operating observability at pb-scale ingestion and hundreds of millions of series. 

• Expertise in observability platforms and tooling (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, ClickHouse) and standards (OpenTelemetry, OpenMetrics).  

• Deep experience building systems of scale and operating cloud infrastructure with Kubernetes; strong proficiency with service mesh technologies (Istio/Envoy), infrastructure‑as‑code (Terraform) and experience in multi‑cloud (AWS, GCP) 

• Demonstrated ability to evolve storage and query architectures for cost, scale, and latency (e.g., TSDB, Parquet, distributed processing). 

• Proven experience integrating security as part of infrastructure and platform development.   

• Exceptional cross‑functional communication; effective collaboration with both technical and non‑technical stakeholders. 

• Culture fit: independent thinker, pragmatic problem‑solver, low‑ego collaborator who moves fast and focuses on company success. 

• Experience integrating AI tools to improve processes and reduce toil. 
• Open‑source contributions in CNCF projects is preferred but not mandatory.  

#LI-PA1

About the team

You will be part of the Roku Video Platform Engineering team and responsible for building the next-generation video services for the Roku Cloud TV Platform. Roku pioneered TV streaming and continues to innovate and lead the industry. The Roku Channel has us well-positioned to help shape the future of streaming. Continued success relies on investing in the Roku Cloud TV Platform to deliver a high-quality streaming TV experience on a global scale. 

About the role

As a Video Encoding Engineer, you will build, optimize, and maintain high-performance video processing workflows. You will own our end-to-end encoding toolchain—from experimentation and profile tuning to automated packaging workflows—ensuring our content is delivered with maximum quality, reliability, and efficiency.

You will work closely with the team on key video services projects around video ingestion, encoding, VoD/live-linear, Server-Side Ads Insertion, and Video QoS, with the goal of delivering a best-in-class streaming TV experience across all Roku devices. The projects that you will work on will impact millions of Roku users around the world. Throughout, you will have the opportunity to collaborate with key product engineering stakeholders across Roku engineering teams and to lead the design of our video services platform.

The ideal candidate will have endless curiosity and can pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can drive programs with the product and commercial teams within Roku and across external strategic partner organizations. The successful candidate will display a balance of hard and soft skills, including the ability to respond quickly to changing business needs. 

What you’ll be doing

• Design, build, optimize, and maintain FFmpeg-based encoding pipelines for both VOD and Live workflows, operating at scale in cloud environments such as AWS or GCP
• Develop, refine, and validate encoding presets for modern codecs, including H.264, HEVC, and AV1, ensuring optimal quality-to-bitrate performance
• Implement advanced encoding strategies such as multi-pass workflows, CRF tuning, per-title optimizations, and quality-targeted encoding
• Benchmark and evaluate video quality using VMAF and other objective metrics to drive continuous improvements in efficiency and viewing experience
• Build and maintain adaptive streaming packaging workflows, including HLS, DASH, and CMAF, ensuring broad device compatibility and reliable playback
• Profile and optimize system performance by identifying and eliminating bottlenecks across compute, storage, and I/O layers
• Write, review, and improve code, assessing architectural tradeoffs to deliver secure, high-performance, and highly concurrent video infrastructure services
• Collaborate cross-functionally with engineering, product, and platform teams to support and advance company-wide video service initiatives

We’re excited if you have

• Strong problem-solving and analytical abilities
• 5+ years of solid programming experience and passionate about writing high-quality and well-architected code
• Expert-level knowledge of FFmpeg or Gstreamer and their related toolchains (filters, flags, debugging, custom builds)
• Experience with hardware-based encoder/decoder libraries (NVENC, Vulkan
• Strong understanding of compression theory, codec internals, GOP structures, bitrate control, etc
• Experience with container formats: MP4, TS, fragmented MP4, ISOBMFF
• Familiarity with HLS/DASH, CMAF, adaptive bitrate design, DRM, and SCTE 35
• A track record working with applied AI-based video enhancement and compression algorithms (Super Resolution, Denoising, Artifact Removal)
• Hands-on experience with cloud compute (AWS Lambda/ECS/Batch, GCP, Kubernetes, or similar)
• Ability to handle periodic on-call duty as well as out-of-band requests; strong written and verbal communication skills
• Bachelor's degree in computer science plus 8 years of experience or equivalent; Master's degree preferred 

#LI-SB-5

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 

The Roku trust engineering team is a close knit group of professionals with a passion for information security.  Our mission is to protect our customers, partners, devices, services, infrastructure, and data. We work collaboratively, sharing insights and expertise to stay ahead of the curve. Join us, and you’ll be part of a dynamic team that thrives on challenges and celebrates victories together. 

About The Role  

As a Senior Security Engineer on the Trust Cloud team, your role involves evaluating, architecting, designing, and implementing end-to-end security controls to impact the global user base. A key focus is on developing automated, scalable security solutions to enhance efficiency and protect Roku. This position requires a broad breadth of security expertise across all disciplines of security, including networking, DevSecOps, security tooling implementation, policy and procedure, risk evaluation, etc. 

What You Will Be Doing 

• Conducting enterprise, network, and application level security reviews.
• Conducting threat modelling for infrastructure, platform, and application initiatives.
• Planning and overseeing execution of security initiatives and projects
• Partnering with infrastructure, platform, and application teams to embed security into application architectures and deployment workflows as part of a robust Secure Software Development Lifecycle (SSDLC).
• Improving IAM policies, network configurations, DNS security, and cloud resource management practices.
• Designing and implementing integrations with third-party security platforms to automate vulnerability management, secure secret handling, and cloud posture monitoring, ensuring findings are actionable and seamlessly integrated into engineering workflows.
• Responding to security incidents to triage, contain, remediate, and report.
• Leveraging AI to accelerate your learning and enhance your work products.
• Driving security initiatives end-to-end — from identifying risks to delivering solutions — with high autonomy in a fast-moving environment.
• Automating vulnerability detection, misconfiguration checks, and compliance validation across cloud and containerised environments.
• Creating reusable security automation modules, templates, and patterns for engineering teams to adopt. 

We're Excited If You Have

• Experience doing security consulting and have balanced experience doing hands on implementation
• Experience supporting/leading DevSecOps initiatives and assisting teams in utilising and onboarding onto DSO platforms
• Designing, building, operating, and maintaining DSO platforms through IaC
• Offensive cyber operations such as application, system, and network level penetration testing
• Software Engineering experience with at least one general purpose programming language (ex. Python, Golang, C, Rust, etc.)
• Developed and/or implemented data tagging, data catalogs, or other data protection related activities
• Experience designing and administering enterprise identity and access management solutions at scale (ex: AD, EntraID, Okta, etc)
• Experience securely running and operating web applications, web services, and service-oriented architecture in production environments.
• A proven track record of deploying and operating Kubernetes clusters in production.  
• Experience deploying and operating infrastructure in multiple cloud providers (AWS, GCP, Azure)
• Fleet administration of Linux workstations and servers
• Defensive cyber operations such as operating a SEIM, managing a SOC, or leading cyber investigations 

#LI-AM3

About The Team 

The Roku trust engineering team is a close knit group of professionals with a passion for information security.  Our mission is to protect our customers, partners, devices, services, infrastructure, and data. We work collaboratively, sharing insights and expertise to stay ahead of the curve. Join us, and you’ll be part of a dynamic team that thrives on challenges and celebrates victories together. 

About The Role  

As a Senior Security Engineer on the Trust Cloud team, your role involves evaluating, architecting, designing, and implementing end-to-end security controls to impact the global user base. A key focus is on developing automated, scalable security solutions to enhance efficiency and protect Roku. This position requires a broad breadth of security expertise across all disciplines of security, including networking, DevSecOps, security tooling implementation, policy and procedure, risk evaluation, etc. 

What You Will Be Doing 

• Conducting enterprise, network, and application level security reviews.
• Conducting threat modelling for infrastructure, platform, and application initiatives.
• Planning and overseeing execution of security initiatives and projects
• Partnering with infrastructure, platform, and application teams to embed security into application architectures and deployment workflows as part of a robust Secure Software Development Lifecycle (SSDLC).
• Improving IAM policies, network configurations, DNS security, and cloud resource management practices.
• Designing and implementing integrations with third-party security platforms to automate vulnerability management, secure secret handling, and cloud posture monitoring, ensuring findings are actionable and seamlessly integrated into engineering workflows.
• Responding to security incidents to triage, contain, remediate, and report.
• Leveraging AI to accelerate your learning and enhance your work products.
• Driving security initiatives end-to-end — from identifying risks to delivering solutions — with high autonomy in a fast-moving environment.
• Automating vulnerability detection, misconfiguration checks, and compliance validation across cloud and containerised environments.
• Creating reusable security automation modules, templates, and patterns for engineering teams to adopt. 

We're Excited If You Have

• Experience doing security consulting and have balanced experience doing hands on implementation
• Experience supporting/leading DevSecOps initiatives and assisting teams in utilising and onboarding onto DSO platforms
• Designing, building, operating, and maintaining DSO platforms through IaC
• Offensive cyber operations such as application, system, and network level penetration testing
• Software Engineering experience with at least one general purpose programming language (ex. Python, Golang, C, Rust, etc.)
• Developed and/or implemented data tagging, data catalogs, or other data protection related activities
• Experience designing and administering enterprise identity and access management solutions at scale (ex: AD, EntraID, Okta, etc)
• Experience securely running and operating web applications, web services, and service-oriented architecture in production environments.
• A proven track record of deploying and operating Kubernetes clusters in production.  
• Experience deploying and operating infrastructure in multiple cloud providers (AWS, GCP, Azure)
• Fleet administration of Linux workstations and servers
• Defensive cyber operations such as operating a SEIM, managing a SOC, or leading cyber investigations 

#LI-AM3

Are you passionate about building scalable, high-performance systems that process massive amounts of data? Do you thrive on designing and implementing innovative solutions to empower engineering teams with actionable insights? Are you excited to advance open-source observability at a massive scale? Join us to extend (open source) observability tools and build new capabilities that help teams manage data better and get actionable insights. 

About the Team 

The Observability team is part of Roku’s Cloud Technology Infrastructure organisation and plays a critical role in our platform. We are a high-performing, fast-moving international team that thrives on ownership, effective communication, and delivering impactful engineering solutions. 

Our mission is to advance Roku’s observability platform, which operates at an impressive scale by ingesting terabytes of data daily and managing hundreds of millions of active series. As part of this mission, we focus on building scalable, performant systems to meet Roku’s unique needs. By leveraging open-source tools, CNCF-supported projects, and custom solutions, we enable engineering teams across Roku to monitor, debug, and optimize their applications with ease. 

What sets us apart is our results-driven culture rooted in ownership, accountability, and fast iteration. We prioritize solving meaningful engineering problems, fostering collaboration, and continuously improving how we work as a team. 

About the Role 

You will work on core observability systems (metrics, logs, traces) while also developing robust data pipelines and storage solutions optimized for high throughput, performance, and cost. You’ll leverage technologies such as time-series databases (TSDB), columnar storage formats (e.g., Parquet), and distributed data processing frameworks to advance the platform’s capabilities. Collaboration with cross-functional teams will be critical, as you’ll integrate observability into Roku’s cloud-native stack and contribute improvements back to the open-source community. 

• Extend and integrate open-source observability systems, and when needed, structurally overhaul core components, such as storage layers and query paths, to improve performance, reliability, and usability of these tools at scale. 

• Build services to improve performance, usability, reliability, and cost efficiency. 

• Implement features like pre-aggregation, downsampling, and sampling to reduce load and accelerate queries. 

• Create developer-facing capabilities for metrics, logs, and traces usage, data quality, and cost management. 

• Automate onboarding, dashboards, alerting, and tracing. 

• Collaborate across platform and infrastructure teams to integrate observability into Roku’s cloud-native stack. 

What We’re Looking For 

• Extensive experience in software engineering building distributed, high-throughput systems or observability platforms. 

• Hands on Go experience; our observability ecosystem is Go-based, making it the most effective language for this role. 

• Experience with, or strong interest in, observability tools (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Clickhouse) and standards (OpenTelemetry, OpenTracing, OpenMetrics). 

• Deep understanding of distributed systems and data models 

• Hands-on experience with Kubernetes, and cloud platforms (AWS, GCP, Azure). 

#LI-PA1

Are you passionate about building scalable, high-performance systems that process massive amounts of data? Do you thrive on designing and implementing innovative solutions to empower engineering teams with actionable insights? Are you excited to advance open-source observability at a massive scale? Join us to extend (open source) observability tools and build new capabilities that help teams manage data better and get actionable insights. 

About the Team 

The Observability team is part of Roku’s Cloud Technology Infrastructure organisation and plays a critical role in our platform. We are a high-performing, fast-moving international team that thrives on ownership, effective communication, and delivering impactful engineering solutions. 

Our mission is to advance Roku’s observability platform, which operates at an impressive scale by ingesting terabytes of data daily and managing hundreds of millions of active series. As part of this mission, we focus on building scalable, performant systems to meet Roku’s unique needs. By leveraging open-source tools, CNCF-supported projects, and custom solutions, we enable engineering teams across Roku to monitor, debug, and optimise their applications with ease. 

What sets us apart is our results-driven culture rooted in ownership, accountability, and fast iteration. We prioritise solving meaningful engineering problems, fostering collaboration, and continuously improving how we work as a team. 

About the Role 

You will work on core observability systems (metrics, logs, traces) while also developing robust data pipelines and storage solutions optimized for high throughput, performance, and cost. You’ll leverage technologies such as time-series databases (TSDB), columnar storage formats (e.g., Parquet), and distributed data processing frameworks to advance the platform’s capabilities. Collaboration with cross-functional teams will be critical, as you’ll integrate observability into Roku’s cloud-native stack and contribute improvements back to the open-source community. 

• Extend and integrate open-source observability systems, and when needed, structurally overhaul core components, such as storage layers and query paths, to improve performance, reliability, and usability of these tools at scale. 

• Build services to improve performance, usability, reliability, and cost efficiency. 

• Implement features like pre-aggregation, downsampling, and sampling to reduce load and accelerate queries. 

• Create developer-facing capabilities for metrics, logs, and traces usage, data quality, and cost management. 

• Automate onboarding, dashboards, alerting, and tracing. 

• Collaborate across platform and infrastructure teams to integrate observability into Roku’s cloud-native stack. 

What We’re Looking For 

• Extensive experience in software engineering building distributed, high-throughput systems or observability platforms. 

• Hands on Go experience; our observability ecosystem is Go-based, making it the most effective language for this role. 

• Experience with, or strong interest in, observability tools (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Clickhouse) and standards (OpenTelemetry, OpenTracing, OpenMetrics). 

• Deep understanding of distributed systems and data models 

• Hands-on experience with Kubernetes, and cloud platforms (AWS, GCP, Azure). 

#LI-PA1

Are you passionate about building scalable, high-performance systems that process massive amounts of data? Do you thrive on designing and implementing innovative solutions to empower engineering teams with actionable insights? Are you excited to advance open-source observability at a massive scale? Join us to extend (open source) observability tools and build new capabilities that help teams manage data better and get actionable insights. 

About the Team 

The Observability team is part of Roku’s Cloud Technology Infrastructure organisation and plays a critical role in our platform. We are a high-performing, fast-moving international team that thrives on ownership, effective communication, and delivering impactful engineering solutions. 

Our mission is to advance Roku’s observability platform, which operates at an impressive scale by ingesting terabytes of data daily and managing hundreds of millions of active series. As part of this mission, we focus on building scalable, performant systems to meet Roku’s unique needs. By leveraging open-source tools, CNCF-supported projects, and custom solutions, we enable engineering teams across Roku to monitor, debug, and optimise their applications with ease. 

What sets us apart is our results-driven culture rooted in ownership, accountability, and fast iteration. We prioritise solving meaningful engineering problems, fostering collaboration, and continuously improving how we work as a team. 

About the Role 

You will work on core observability systems (metrics, logs, traces) while also developing robust data pipelines and storage solutions optimized for high throughput, performance, and cost. You’ll leverage technologies such as time-series databases (TSDB), columnar storage formats (e.g., Parquet), and distributed data processing frameworks to advance the platform’s capabilities. Collaboration with cross-functional teams will be critical, as you’ll integrate observability into Roku’s cloud-native stack and contribute improvements back to the open-source community. 

• Extend and integrate open-source observability systems, and when needed, structurally overhaul core components, such as storage layers and query paths, to improve performance, reliability, and usability of these tools at scale. 

• Build services to improve performance, usability, reliability, and cost efficiency. 

• Implement features like pre-aggregation, downsampling, and sampling to reduce load and accelerate queries. 

• Create developer-facing capabilities for metrics, logs, and traces usage, data quality, and cost management. 

• Automate onboarding, dashboards, alerting, and tracing. 

• Collaborate across platform and infrastructure teams to integrate observability into Roku’s cloud-native stack. 

What We’re Looking For 

• Extensive experience in software engineering building distributed, high-throughput systems or observability platforms. 

• Hands on Go experience; our observability ecosystem is Go-based, making it the most effective language for this role. 

• Experience with, or strong interest in, observability tools (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Clickhouse) and standards (OpenTelemetry, OpenTracing, OpenMetrics). 

• Deep understanding of distributed systems and data models 

• Hands-on experience with Kubernetes, and cloud platforms (AWS, GCP, Azure). 

#LI-PA1

Are you passionate about building scalable, high-performance systems that process massive amounts of data? Do you thrive on designing and implementing innovative solutions to empower engineering teams with actionable insights? Are you excited to advance open-source observability at a massive scale? Join us to extend (open source) observability tools and build new capabilities that help teams manage data better and get actionable insights. 

About the Team 

The Observability team is part of Roku’s Cloud Technology Infrastructure organisation and plays a critical role in our platform. We are a high-performing, fast-moving international team that thrives on ownership, effective communication, and delivering impactful engineering solutions. 

Our mission is to advance Roku’s observability platform, which operates at an impressive scale by ingesting terabytes of data daily and managing hundreds of millions of active series. As part of this mission, we focus on building scalable, performant systems to meet Roku’s unique needs. By leveraging open-source tools, CNCF-supported projects, and custom solutions, we enable engineering teams across Roku to monitor, debug, and optimise their applications with ease. 

What sets us apart is our results-driven culture rooted in ownership, accountability, and fast iteration. We prioritise solving meaningful engineering problems, fostering collaboration, and continuously improving how we work as a team. 

About the Role 

You will work on core observability systems (metrics, logs, traces) while also developing robust data pipelines and storage solutions optimized for high throughput, performance, and cost. You’ll leverage technologies such as time-series databases (TSDB), columnar storage formats (e.g., Parquet), and distributed data processing frameworks to advance the platform’s capabilities. Collaboration with cross-functional teams will be critical, as you’ll integrate observability into Roku’s cloud-native stack and contribute improvements back to the open-source community. 

• Extend and integrate open-source observability systems, and when needed, structurally overhaul core components, such as storage layers and query paths, to improve performance, reliability, and usability of these tools at scale. 

• Build services to improve performance, usability, reliability, and cost efficiency. 

• Implement features like pre-aggregation, downsampling, and sampling to reduce load and accelerate queries. 

• Create developer-facing capabilities for metrics, logs, and traces usage, data quality, and cost management. 

• Automate onboarding, dashboards, alerting, and tracing. 

• Collaborate across platform and infrastructure teams to integrate observability into Roku’s cloud-native stack. 

What We’re Looking For 

• Extensive experience in software engineering building distributed, high-throughput systems or observability platforms. 

• Hands on Go experience; our observability ecosystem is Go-based, making it the most effective language for this role. 

• Experience with, or strong interest in, observability tools (Prometheus, Grafana, Loki, Tempo, ELK/OpenSearch, Clickhouse) and standards (OpenTelemetry, OpenTracing, OpenMetrics). 

• Deep understanding of distributed systems and data models 

• Hands-on experience with Kubernetes, and cloud platforms (AWS, GCP, Azure). 

#LI-PA1

​​Cloud Engineer is a key role as this will automate, evolve, and establish a scalable cloud platform across the company optimizing for self-service and governance. The role will work with both Cloud Native platforms Azure and AWS, leverage tools like Kubernetes (AKS), and Cloud Hosting providers offerings like IaaS, PaaS, and SaaS ensuring consistent experience and high standards are established.

What will you do?

​​Maintain Microsoft Azure cloud infrastructure​ 

• ​​Utilize best practices to ensure backup and recovery techniques for applications on Azure platform. 
• ​Supporting and maintaining Azure cloud infrastructure 
• ​Implementing deploying workloads on Azure virtual machines 
• ​Container technologies i.e. Kubernetes & AKS  
• ​Utilize Terraform code to deploy multiple resource groups, VMs, and VNETs 
• ​Upgrading version and certificates  
• ​Load Balancers, AzurePolicies, AzureKayVault and Tagging 
• ​Expertise in Microsoft Azure Cloud services (SaaS, PaaS and IaaS) 
• ​Monitoring Azure infrastructure and logs 

​​Maintain Azure cloud AKS​  

• ​​Administration of AKS clusters 
• ​Configuring web apps, Azure App services, Azure DNS, Azure traffic manager, App services and Azure Application gateway, 
• ​Managing the Azure Kubernetes Services policies, providing access to different Azure resources ​managing secrets, firewalls, PODS, containers. 
• ​Injecting data in applications  
• ​Troubleshooting cluster related issues
• ​Cluster AutoScaler and load balancers for Azure Kubernetes Service (AKS) using Terraform and worked with scheduling deploying, and managing pods and replicas in AKS
• Working knowledge in deploying CI/CD system using Azure DevOps and Kubernetes container environment​ 

Azure Automation

• ​​Good knowledge of building and supporting CI/CD pipelines using Azure DevOps 
• ​Creating Ansible play books, Dockers and Jenkins 
• ​Working knowledge on json, yaml, Terraform and Helm chart​ 

After-Hours Support 

• Participate on an on-call rotation and be available for out of office hours support when needed 

What will you need to succeed? 

• Undergraduate degree in Information Technology with MS or AWS Cloud Certification desirable
• 3-5 years of hands-on experience in Azure AKS
• Minimum 3 years of good knowledge in building and supporting CI/CD pipelines using Azure DevOps
• Minimum 4 years Azure Cloud Platform
• Minimum 2 years Azure DevOps experience
• Proficient in Administrating Azure laaS/PaaS, Azure Virtual Machines, VNET, Network services, Azure DevOps,
• Hands on experience on SQL Databases, Storages, AzureActive Directory, Monitoring, Autoscaling,
• Hands on experience in Azure Blueprint, Azure Site Recovery and Azure backup
• PowerSheII Automation, Azure Search, DNS,VPU extensive
• 4+ years’ working experience of Azure SQL and Cloud platform
• Strong understanding of Terraform
• Hands on experience on Load Balancers, AzurePolicies, AzureKayVault and Tagging
• Expertise in Microsoft Azure Cloud services (SAAS, PASS and IAAS)
• Monitoring Azure infrastructure and logs
• Strong knowledge of Azure Networking, Azure Virtual Machines, Azure Active Directory
• Experience with Load Balancers, AzurePolicies, AzureKayVault and Tagging
• Experience with Cloud and other traditional monitoring technologies, as well as hands on experience instrumenting alerts based on aggregated logs and analytics output.

#LI-Hybrid

The expected base salary range for this position is $64,500 - $114,500. Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary. Please note: This range reflects the expected base salary for this role but may not represent the full compensation range for all experience and skill levels. During the recruitment process, we will discuss and consider how your unique qualifications align with the broader range for this position.

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch/JAX.
• Strong Python or C++ software development skills
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator - able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of:
  • MLOps for Kubernetes-based clusters
  • Building production systems with large language models
  • Efficient computing based on low-precision arithmetic.
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Have contributed to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

Senior: PLN 260,400 - 352,200
Staff: PLN 350,700 - 474,400
Subject to alignment to the responsibilities and duties of the role - we currently have multiple positions available at both Senior and Staff level

About Graphcore 

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.

To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.

We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch/JAX.
• Strong Python or C++ software development skills
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator - able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of:
  • MLOps for Kubernetes-based clusters
  • Building production systems with large language models
  • Efficient computing based on low-precision arithmetic.
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Have contributed to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

Benefits

In addition to a competitive salary, Graphcore offers annual leave policy, medical and dental health plans, a gym card, and employee pension (matched up to 4%). We review our benefits on a yearly basis to ensure we offer a valuable and rewarding benefits programme to our employees. We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

About Graphcore 

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.

To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.

We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence

Job Summary

Applicants for this role should have strong experience designing, developing, and maintaining high-quality software systems. The role focuses on testing and validating a complex machine learning software stack, with particular emphasis on software architecture, automation, and engineering best practices.

The ideal candidate is an experienced software engineer who values code quality, testability, and long-term maintainability, and enjoys building systems that other engineers rely on. This person will be comfortable working across large codebases, contributing to CI/CD infrastructure, and shaping technical direction through thoughtful design and mentoring in a technically demanding environment spanning ML frameworks, infrastructure, and AI accelerator hardware

The Team

The ML QA team is composed of highly skilled software engineers with a strong focus on automation, software quality, and data-driven validation. The team works closely with industry-standard machine learning frameworks and models, contributing to upstream open-source projects and collaborating across the wider software organization. 

Operating in a fast-paced environment, the team plays a critical role in ensuring reliability, performance, and maintainability across the ML software stack, helping to deliver robust and high-quality products to customers. 

Responsibilities and Duties

• Design, implement, and maintain robust test infrastructure and automation for a complex ML software stack.
• Architect and evolve test frameworks and tooling with a focus on scalability, maintainability, and developer experience.
• Build and maintain CI/CD pipelines targeting simulators, emulators (e.g. QEMU), and physical hardware.
• Create representative ML workloads and gain insights from their execution. (Numerical accuracy, performance analysis and benchmarking).
• Work closely with all Software development teams, supporting a culture of quality, security and maintainability.
• Review code and designs, setting a high bar for software engineering best practices.
• Mentor and support junior engineers, helping raise the overall technical capability of the team.
• Evaluate existing test strategies and infrastructure, identifying gaps and driving improvements aligned with team and organizational goals. 

Candidate Profile

Essential:

• Experience in production-quality software engineering roles.
• Strong software design and architecture skills, with experience working on large or complex systems.
• Strong proficiency in Python, including experience building and maintaining production codebases.
• Solid experience with CI/CD systems and automated testing (preferably GitHub-based workflows).
• Experience working in Linux environments.
• Familiarity with C or C++, with the ability to read, debug, and reason about low-level code when needed.
• Proven ability to mentor junior engineers and influence engineering practices within a team.
• Strong problem-solving skills and a proactive, self-directed approach to work.
• Bachelor/Master's/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field. 

Desirable

• Exposure to machine learning frameworks such as PyTorch, JAX, Triton, TensorFlow
• Experience with distributed workload management systems such as Kubernetes, VLLM, Keras or MLOps pipelines
• Experience working with hardware simulators or emulators (e.g. QEMU).
• Experience developing for or working with FPGA-based systems.
• Experience with people management or mentoring 

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

About Graphcore 

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute.  

It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.  

As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.   

Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation.  

Job Summary

Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems.

The Team

The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible.

Responsibilities and Duties

• Develop, own, and maintain tools and services to support the software build and release process
• Deploy and maintain services with Kubernetes and Docker
• Manage our Cloud Infrastructure using tools such as Terraform
• Support the technical development of junior and graduate engineer
• Embody a strong engineering discipline for high reliability and minimal toil 

Candidate Profile 

Essential: 

• Knowledge of Python/Go/C++ (or similar language) 

• Experience deploying services in the cloud (AWS preferred) 

• Deep understanding of Linux environments 

• Native user of CI/CD for production deployments 

• Experience with Infrastructure as Code (IaC) tools (e.g. Terraform/OpenTofu) 

Desirable 

• Experience using Kubernetes (k8s) or OpenStack 

• Experience with GitHub Actions 

• Experience with build tools (e.g. CMake) 
• Experience with modern observability tooling (e.g. Prometheus) 
• Experience with Grafana 

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

About Graphcore 

Graphcore is one of the world’s leading innovators in Artificial Intelligence compute.  

It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry.  

As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone.   

Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation.  

Summary 

Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed system

The Team

The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible. 

Responsibilities and Duties 

• Develop, own, and maintain tools and services to support the software org 

• Deploy and maintain Kubernetes infrastructure to develop, test, and scale Graphcore hardware and its software stack 

• Manage our Cloud Infrastructure using tools such as Terraform 

Candidate Profile 

Essential: 

• Practical experience developing in Go 

• Familiarity with cloud services (AWS preferred) 

• Experience managing or developing in Linux environments 

• Understanding of CI/CD principles 

• Strong experience of Kubernetes (k8s) development and deployment 

Desirable 

• Experience developing Kubernetes Controllers 

• Experience with Infrastructure as Code (IaC) tools (e.g. Terraform/OpenTofu) 

• Experience with GitHub Actions 

• Experience with distributed HPC systems 

• Experience with modern observability tooling (e.g. Prometheus) 

• Knowledge of Python/C++ (or similar language) 

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch/JAX.
• Strong Python or C++ software development skills
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator - able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of:
  • MLOps for Kubernetes-based clusters
  • Building production systems with large language models
  • Efficient computing based on low-precision arithmetic.
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Have contributed to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

About Graphcore 

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.

To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.

We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence

Job Summary

As a member of the drivers and utilities team you will contribute to the planning, design, implementation and testing of low level kernel drivers and user space driver library code. You will be part of one of the two teams in the system software department (the firmware team being the other one) and report to the drivers and utilities team manager.  

The Team

The drivers and utilities team forms part of the system software group – working closely with both software engineers developing our Poplar SDK and with silicon and hardware engineers developing Graphcore’s IPU solution. The drivers and utilities team develop custom control software on the host in kernel and user space. Our solutions enable our customers to get maximum performance and utility for our cutting-edge products.  

Responsibilities and Duties

• Design, implement, test and document OS Kernel and Device Driver software at the highest standard using C/C++/Python programming languages
• Participate in agile development – working as part of a scrum team to develop the right software at pace
• Communicate effectively and contribute regularly to technical discussions with your peers in software and hardware engineering, with architects and other stakeholders
• Hands-on during key product development phases involving close working with hardware and silicon engineering groups to enable fast time to market delivery

Candidate Profile

Essential:

• Proven industry experience in software development using programming languages such as C/C++/Python
• OS Kernel and Device Driver development and deployment experience in Linux or Windows systems
• Good understanding of lower-level software stack and interactions with the hardware layer
• Possess effective problem-solving skills, familiar with a full suite of debug and performance analysis tools and techniques
• Experience with one or more of the following: PCIe, CPU, device drivers, SoC, firmware, and hardware/software integration
• Proactive in obtaining engineering or management input to solve issues
• Motivated to schedule own workload
• Excellent written and verbal communication skills, work well within a multinational team and with multinational customers. Excellent cultural awareness is essential. 

Desirable

• Experience developing firmware or drivers for GPUs. 
• Knowledge of CUDA or OpenCL  
• Experience working on upstreaming of kernel code / contributing to Linux kernel.
• Exposure to integration with data centre / cloud service operations – for example integration with Kubernetes or open stack. 

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.  

Job Summary

As a Senior Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. You will work on large scale systems where performance is critical to the success of our projects. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. We seek engineers with strong technical skills and an understanding of AI model implementation at scale, eager to make a tangible impact in this rapidly evolving field.

The Team

The Applied AI team’s role is to be proxies for our customers, we need to understand the latest AI models, applications, and software to ensure that Graphcore’s technology works seamlessly with the AI ecosystem and at scale. We build reference applications, contribute to key software libraries e.g. optimising kernels for efficiency on our hardware, and collaborate with the Research team to develop and publish novel ideas in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications.

If you're excited about advancing the next generation of AI models on cutting-edge hardware, we’d love to hear from you!

Responsibilities and Duties

• Implement latest machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators.
• Test and evaluate new internal software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews.
• Benchmark models and key ML techniques to identify performance bottlenecks and improve model efficiency.
• Design and conduct experiments on novel AI methods, implement them and evaluate results.
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware.
• Engage with AI community and keep in touch with the latest developments in AI.

Candidate Profile

Essential:

• Bachelor/Master's/PhD or equivalent experience in Machine Learning, Computer Science, Maths, Data Science, or related field.
• Proficiency in deep learning frameworks like PyTorch/JAX.
• Strong Python or C++ software development skills
• Expertise in deep learning from model training to optimisation and evaluation.
• Experience in distributed training or inference of ML models across 64+ accelerators.
• Capable of designing, executing and reporting from ML experiments.
• Developed deep understanding of performance bottlenecks and how to overcome them.
• Ability to move quickly in a dynamic environment
• Enjoy cross-functional work collaborating with other teams.
• Strong communicator - able to explain complex technical concepts to different audiences.

Desirable:

• Experience in one or more of:
  • MLOps for Kubernetes-based clusters
  • Building production systems with large language models
  • Efficient computing based on low-precision arithmetic.
• Experience writing C++/Triton/CUDA kernels for performance optimisation of ML models.
• Familiarity with HPC systems and networking including Infiniband, NVLink, RoCE technologies.
• Have contributed to open-source projects or published research papers in relevant fields.
• Knowledge of cloud computing platforms.
• Keen to present, publish and deliver talks in the AI community.

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

About Graphcore 

At Graphcore, we’re building the future of AI compute.

We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.

As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary 

Join our dynamic Software Infrastructure team and take a pivotal role in scaling and managing our infrastructure. You will develop essential tools and services that empower our broader software team. Your contributions will enhance the build, test, deployment, and productisation processes of our Machine Learning Software components. Work with our High-Performance Computing (HPC) AI platforms and gain invaluable experience in distributed systems

The Team

The Software Infrastructure team provides critical platforms and services for software development teams across the business. Our responsibilities include managing the CI platform and services, build engineering, component integration, and packaging and release systems. We operate in squads, fostering a culture of service ownership and empowerment for our engineers. We focus on long-term engineering solutions and strive to eliminate toil wherever possible. 

Responsibilities and Duties 

• Develop, own, and maintain tools and services to support AI research and engineering teams 

• Deploy and maintain services with Kubernetes and Docker 

• Manage our Cloud Infrastructure using tools such as Terraform 

Candidate Profile  

Essential: 

• Knowledge of Python 

• Familiarity with cloud services (e.g. AWS) 

• Experience managing or developing in Linux environments 

• Understanding of CI/CD principles 

• Experience using Kubernetes (k8s) 
  
• Experience of one of the following:
  
  
• maintaining machine learning applications.
  
  
• deploying ML orchestration tools (e.g. NV Ray, KFP, SkyPilot).
  
  
• managing ML accelerator hardware (e.g. DCGM).

Desirable 

• Experience with Infrastructure as Code (IaC) tools (e.g. Terraform/OpenTofu) 

• Experience with GitHub Actions 

• Experience with modern observability tooling (e.g. Prometheus) 

• Experience with Grafana 

• Knowledge of Go/Java/C++ (or similar language)

  Benefits

  In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

  Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

MORSE is seeking a skilled Full Stack Software Engineer to join one or more projects in big data, artificial intelligence, autonomous vehicle mission planning, decision systems, and their accompanying cloud applications. Our applications provide cutting-edge, algorithmic-based simulation, situational awareness, machine learning, analysis, and mission planning capabilities to a wide variety of DoD customers. As a member of a small interdisciplinary team of scientists, engineers, and software developers, you will follow Agile development processes and embrace DevSecOps to ensure fast and secure delivery of software services.

Responsibilities:

• Develop and maintain web applications hosted on cloud infrastructure

• Collaborate with infrastructure engineers to containerize applications for cloud deployment

• Implement web page UIs from design documents

• Write backend APIs that interact with cloud services

• Work closely with team members to design, develop, and deploy software applications

• Stay up-to-date with the latest web development and cloud computing trends

• Contribute to the development of new code bases that are heavily object-oriented, extensible, and maintainable

Requirements:

• U.S. Citizenship and the ability to obtain a U.S. Security Clearance (Secret or Top Secret)

• 5+ years of software engineering experience

• Experience with React and front end development

• Experience with Python

• Knowledge of Cloud technologies, including AWS, Azure, or GCP

• Proficiency with Docker and Kubernetes

• Experience with Agile development

• BS or MS in computer science or equivalent degree, or significant professional experience

Desired Skills:

• Experience with HCI and web design

• Experience with microservice architecture

• Experience with IAC tools like Terraform or CloudFormation

• Experience with scalable cloud infrastructure

MORSE is seeking a skilled Full Stack Software Engineer to join one or more projects in big data, artificial intelligence, autonomous vehicle mission planning, decision systems, and their accompanying cloud applications. Our applications provide cutting-edge, algorithmic-based simulation, situational awareness, machine learning, analysis, and mission planning capabilities to a wide variety of DoD customers. As a member of a small interdisciplinary team of scientists, engineers, and software developers, you will follow Agile development processes and embrace DevSecOps to ensure fast and secure delivery of software services.

Responsibilities:

• Develop and maintain web applications hosted on cloud infrastructure

• Collaborate with infrastructure engineers to containerize applications for cloud deployment

• Implement web page UIs from design documents

• Write backend APIs that interact with cloud services

• Work closely with team members to design, develop, and deploy software applications

• Stay up-to-date with the latest web development and cloud computing trends

• Contribute to the development of new code bases that are heavily object-oriented, extensible, and maintainable

Requirements:

• U.S. Citizenship and the ability to obtain a U.S. Security Clearance (Secret or Top Secret)

• 5+ years of software engineering experience

• Experience with React and front end development

• Experience with Python

• Knowledge of Cloud technologies, including AWS, Azure, or GCP

• Proficiency with Docker and Kubernetes

• Experience with Agile development

• BS or MS in computer science or equivalent degree, or significant professional experience

Desired Skills:

• Experience with HCI and web design

• Experience with microservice architecture

• Experience with IAC tools like Terraform or CloudFormation

• Experience with scalable cloud infrastructure

MORSE is seeking a skilled Full Stack Software Engineer to join one or more projects in big data, artificial intelligence, autonomous vehicle mission planning, decision systems, and their accompanying cloud applications. Our applications provide cutting-edge, algorithmic-based simulation, situational awareness, machine learning, analysis, and mission planning capabilities to a wide variety of DoD customers. As a member of a small interdisciplinary team of scientists, engineers, and software developers, you will follow Agile development processes and embrace DevSecOps to ensure fast and secure delivery of software services.

Responsibilities:

• Develop and maintain web applications hosted on cloud infrastructure

• Collaborate with infrastructure engineers to containerize applications for cloud deployment

• Implement web page UIs from design documents

• Write backend APIs that interact with cloud services

• Work closely with team members to design, develop, and deploy software applications

• Stay up-to-date with the latest web development and cloud computing trends

• Contribute to the development of new code bases that are heavily object-oriented, extensible, and maintainable

Requirements:

• U.S. Citizenship and the ability to obtain a U.S. Security Clearance (Secret or Top Secret)

• 5+ years of software engineering experience

• Experience with React and front end development

• Experience with Python

• Knowledge of Cloud technologies, including AWS, Azure, or GCP

• Proficiency with Docker and Kubernetes

• Experience with Agile development

• BS or MS in computer science or equivalent degree, or significant professional experience

Desired Skills:

• Experience with HCI and web design

• Experience with microservice architecture

• Experience with IAC tools like Terraform or CloudFormation

• Experience with scalable cloud infrastructure

MORSE is seeking highly motivated and talented Python Software Engineers to join our innovative team, supporting various projects that provide critical AI, machine learning, simulation, situational awareness, and mission planning capabilities to a diverse range of Department of Defense (DoD) customers.

As a Python Software Engineer at MORSE, you will have the opportunity to work on cutting-edge technology, contributing to the success of our applications and making a meaningful impact on our customers. You will collaborate with a teams of engineers and data scientists to design, develop, and deliver high-quality software products that meet the highest standards of quality, scalability, and reliability.

Responsibilities:

• Design and develop scalable, efficient, and reliable software applications using Python 

• Participate in design reviews, code reviews, and pair programming to ensure high-quality code and knowledge sharing

• Stay up-to-date with the latest software engineering trends, tools, and technologies

• Collaborate with cross-functional teams to deliver high-quality software products, ensuring seamless integration and deployment

• Contribute to the development of new codebases that emphasize object-orientation, modularity, and maintainability

Requirements:

• US citizenship and the ability to obtain a U.S. security clearance (Secret, Top Secret, or TS/SCI)

• Expertise in Python 

• Strong understanding of relational databases and version control systems (e.g., Git)

• Experience with Docker, Docker-compose, or Kubernetes

• Familiarity with Agile development methodologies (Scrum or Kanban) and microservice architecture

• Strong communication skills and self-motivation

• Bachelor's or Master's degree in Computer Science or a related field (or significant professional experience)

• 5+ years of software development experience

Preferred Qualifications:

• Experience with cloud computing platforms (AWS, Azure, GCP)

• Knowledge of Spark or PySpark

• Background in mathematics or computer science

• Experience with DevOps tools and practices

• Familiarity with containerization technologies 

• Experience or desire to lead technical teams

MORSE is seeking highly motivated and talented Software Engineers with Cloud skills to join our innovative team, supporting various projects that provide critical AI, machine learning, simulation, situational awareness, and mission planning capabilities to a diverse range of Department of Defense (DoD) customers.

As a Cloud Software Engineer at MORSE, you will have the opportunity to work on cutting-edge technology, contributing to the success of our applications and making a meaningful impact on our customers. You will collaborate with a teams of engineers and data scientists to design, develop, and deliver high-quality software products that meet the highest standards of quality, scalability, and reliability.

Responsibilities:

• Design and develop scalable, efficient, and reliable software applications using Python 

• Develop and maintain cloud infrastructure 

• oversee the deployment of cloud services and compliance to security guidelines

• Participate in design reviews, code reviews, and pair programming to ensure high-quality code and knowledge sharing

• Stay up-to-date with the latest software engineering trends, tools, and technologies

• Collaborate with cross-functional teams to deliver high-quality software products, ensuring seamless integration and deployment

• Contribute to the development of new codebases that emphasize object-orientation, modularity, and maintainability

Requirements:

• US citizenship and the ability to obtain a U.S. security clearance (Secret, Top Secret, or TS/SCI)

• Expertise in Python 

• 1+ years of experience working with AWS, Azure or GCP.

• Experience with Terraform or Cloud Formation

• Strong understanding of relational databases and version control systems (e.g., Git)

• Experience with Docker, Docker-compose, or Kubernetes

• Familiarity with Agile development methodologies (Scrum or Kanban) and microservice architecture

• Strong communication skills and self-motivation

• Bachelor's or Master's degree in Computer Science or a related field (or significant professional experience)

• 3+ years of software development experience

MORSE is seeking highly motivated and talented Software Engineers with Cloud skills to join our innovative team, supporting various projects that provide critical AI, machine learning, simulation, situational awareness, and mission planning capabilities to a diverse range of Department of Defense (DoD) customers.

As a Cloud Software Engineer at MORSE, you will have the opportunity to work on cutting-edge technology, contributing to the success of our applications and making a meaningful impact on our customers. You will collaborate with a teams of engineers and data scientists to design, develop, and deliver high-quality software products that meet the highest standards of quality, scalability, and reliability.

Responsibilities:

• Design and develop scalable, efficient, and reliable software applications using Python 

• Develop and maintain cloud infrastructure 

• oversee the deployment of cloud services and compliance to security guidelines

• Participate in design reviews, code reviews, and pair programming to ensure high-quality code and knowledge sharing

• Stay up-to-date with the latest software engineering trends, tools, and technologies

• Collaborate with cross-functional teams to deliver high-quality software products, ensuring seamless integration and deployment

• Contribute to the development of new codebases that emphasize object-orientation, modularity, and maintainability

Requirements:

• US citizenship and the ability to obtain a U.S. security clearance (Secret, Top Secret, or TS/SCI)

• Expertise in Python 

• 1+ years of experience working with AWS, Azure or GCP.

• Experience with Terraform or Cloud Formation

• Strong understanding of relational databases and version control systems (e.g., Git)

• Experience with Docker, Docker-compose, or Kubernetes

• Familiarity with Agile development methodologies (Scrum or Kanban) and microservice architecture

• Strong communication skills and self-motivation

• Bachelor's or Master's degree in Computer Science or a related field (or significant professional experience)

• 3+ years of software development experience

MORSE is seeking highly motivated and talented Python Software Engineers to join our innovative team, supporting various projects that provide critical AI, machine learning, simulation, situational awareness, and mission planning capabilities to a diverse range of Department of Defense (DoD) customers.

As a Python Software Engineer at MORSE, you will have the opportunity to work on cutting-edge technology, contributing to the success of our applications and making a meaningful impact on our customers. You will collaborate with a teams of engineers and data scientists to design, develop, and deliver high-quality software products that meet the highest standards of quality, scalability, and reliability.

Responsibilities:

• Design and develop scalable, efficient, and reliable software applications using Python 

• Participate in design reviews, code reviews, and pair programming to ensure high-quality code and knowledge sharing

• Stay up-to-date with the latest software engineering trends, tools, and technologies

• Collaborate with cross-functional teams to deliver high-quality software products, ensuring seamless integration and deployment

• Contribute to the development of new codebases that emphasize object-orientation, modularity, and maintainability

Requirements:

• US citizenship and the ability to obtain a U.S. security clearance (Secret, Top Secret, or TS/SCI)

• Expertise in Python 

• Strong understanding of relational databases and version control systems (e.g., Git)

• Experience with Docker, Docker-compose, or Kubernetes

• Familiarity with Agile development methodologies (Scrum or Kanban) and microservice architecture

• Strong communication skills and self-motivation

• Bachelor's or Master's degree in Computer Science or a related field (or significant professional experience)

• 5+ years of software development experience

Preferred Qualifications:

• Experience with cloud computing platforms (AWS, Azure, GCP)

• Knowledge of Spark or PySpark

• Background in mathematics or computer science

• Experience with DevOps tools and practices

• Familiarity with containerization technologies 

• Experience or desire to lead technical teams

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Your Impact at LILA

Join us in shaping the future of science! We are seeking Sr Principal, and Principal Software Engineers with full stack experience to join our software org, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. Our teams span across App, Data, SSR, and LaS with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

Our Software Teams

The Application Team (App)- They build the operating system for AI-driven science. Their platform unifies Machine Learning, Life Sciences, Physical Sciences, and Software into one AI-native experience — where a scientist can go from hypothesis to experiment to result in a single conversation. They ship the agents, the integrations, and the interfaces that make that possible.

The Scientific System of Record Team (SSR) - They build the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

The Lab as Software Team (LaS)- They act as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.

The Data Platform Team (Data)- They build and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You'll Need To Succeed  

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8-15 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
• Hands on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware drivers.

Your Impact at LILA

Join us in shaping the future of science! We are seeking Staff, Senior II, and Senior I Software Engineers with either frontend or backend experience to join our software org, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. Our teams span across App, Data, SSR, and LaS with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

Our Software Teams

The Application Team (App)- They build the operating system for AI-driven science. Their platform unifies Machine Learning, Life Sciences, Physical Sciences, and Software into one AI-native experience — where a scientist can go from hypothesis to experiment to result in a single conversation. They ship the agents, the integrations, and the interfaces that make that possible.

The Scientific System of Record Team (SSR) - They build the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

The Lab as Software Team (LaS)- They act as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab.

The Data Platform Team (Data)- They build and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter.

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5-10 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend.
• Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
• Hands on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
• Experience with laboratory devices, robotics, or hardware drivers.

Your Impact at LILA

We are seeking a Senior Software Engineer to join our Applied AI group and help build the next generation of our AI-driven scientific platform. In this role, you will design and optimize the backend systems, data pipelines, and AI integrations that power intelligent, data-driven applications. You’ll work at the intersection of backend engineering and machine learning, ensuring our platform seamlessly scales and supports cutting-edge applied AI techniques such as Retrieval-Augmented Generation (RAG), agentic AI, and large language model (LLM) integration.

This role is ideal for someone who thrives in bridging software engineering and applied AI—turning research into production-grade systems that drive real-world scientific discovery. If you are passionate about building performant, elegant systems that make AI useful and impactful, we would love to hear from you!

What You'll Be Building

• Applied AI Integration: Design and deploy backend services and data pipelines that directly support advanced AI applications, including LLMs, RAG, and agentic frameworks.
• API & Service Development: Build high-performance APIs and microservices that enable seamless integration between AI models, scientific tools, and user-facing applications.
• Data Pipeline Architecture: Architect and manage scalable pipelines capable of handling structured, unstructured, and vectorized data for AI/ML workloads.
• Database & Knowledge Systems: Implement and optimize SQL, NoSQL, and vector databases to support low-latency AI retrieval and inference workloads.
• Cloud & Infrastructure: Leverage AWS, Kubernetes, and infrastructure-as-code (Terraform/CloudFormation) to build robust, production-ready AI platforms.
• Performance & Reliability: Diagnose system bottlenecks, optimize for cost and speed, and ensure the reliability and fault-tolerance of AI-driven workflows.
• Collaboration: Partner with ML researchers, platform engineers, and scientists to translate models and algorithms into scalable, production-ready systems.

What You’ll Need to Succeed

• Educational Background: Bachelor’s or Master’s in Computer Science, Engineering, or a related field.
• Backend & Data Expertise: 7+ years of professional experience building and scaling production systems, including APIs, data pipelines, and distributed services.
• Programming Skills: Strong Python skills (FastAPI, Flask, Django), with solid experience in backend service development.
• Databases: Proven experience with SQL, NoSQL, and vector databases; skilled in schema design, indexing, and query optimization.
• Applied AI Systems: Hands-on experience integrating ML models or AI-driven workflows into production services.
• Cloud & DevOps: Proficiency with AWS, Docker/Kubernetes, CI/CD pipelines, and infrastructure-as-code.
• Communication & Problem-Solving: Ability to work cross-functionally with diverse teams and explain complex technical concepts to non-experts.

Bonus Points For

• Scientific & Data-Intensive Domains: Experience working with life sciences, materials sciences, or other research-heavy fields.
• Startup Experience: Comfort with fast-paced, iterative environments where impact and adaptability matter.

Your Impact at LILA

As a member of our team in the Physical Sciences division, you will shape the ML- and agent-driven infrastructure that enables Lila’s scientific superintelligence to autonomously construct, execute, and interpret complex physics simulations. Your work will focus on building the core systems that allow AI agents to reason over and control computational experiments, spanning from electronic structure calculations to surrogate-driven atomistic modeling, and beyond. Your work will directly influence how autonomous computational processes will explore chemical and materials landscapes with unprecedented autonomy and robustness.

What You'll Be Building

• Architect and implement agentic frameworks that support dynamic, multi-stage simulation workflows for scientific tasks
• Develop pipelines enabling agents to autonomously plan, schedule, execute, and interpret computational tasks at scale
• Build integration layers and APIs that connect ML models, large-scale simulation engines, databases, and heterogeneous compute platforms.
• Work with AI researchers to productionize agent behaviors, including tool-use strategies, simulation-aware decision loops, and adaptive task planning.
• Improve the robustness, modularity, performance, and reproducibility of agent-driven computational workflows; build internal tooling for debugging, observability, and validation.

What You’ll Need to Succeed

• MS/PhD or equivalent experience in Computer Science, ML/AI, Scientific Computing, or a related technical field.
• Strong experience building ML-driven pipelines, workflow systems, or tool-use frameworks, ideally for complex or scientific applications.
• Proficiency in Python and ML ecosystems; experience with one or more compiled languages (e.g., C++, Rust, Julia) is beneficial.
• Familiarity with large-scale scientific or engineering software, including integrating external tools into automated computational workflows.
• Experience with distributed systems, HPC environments, cloud platforms, or accelerator-based computing.
• Deep understanding of modern ML architectures and their deployment in production systems (e.g., GNNs, transformers, diffusion models, multimodal or tool-using models).
• Strong engineering fundamentals: reproducibility, testing, modular design, CI/CD, and scalable ML operations.

Bonus Points For

• Experience developing or integrating agentic frameworks, autonomous ML pipelines, or multi-step tool-using agents, particularly for scientific applications
• Background in large-scale simulation frameworks, scientific workflow orchestration, or automated computational experiment platforms.
• Contributions to open-source ML infrastructure, workflow engines, agent frameworks, or scientific software ecosystems.
• Familiarity with data-centric engineering practices: streaming systems, provenance tracking, distributed metadata services, or large-scale data orchestration.
• Experience with workflow orchestration systems (e.g., Flyte, Prefect, Airflow) and container orchestration (Kubernetes).
• Familiarity with materials science simulation codes (VASP, LAMMPS) or workflow frameworks (atomate, aiida) is a plus but not required.
• Expertise in advanced ML techniques relevant to agentic reasoning (planning models, self-improving systems, multi-tool agents, RLHF/RLAIF workflows).

Your Impact at LILA

We’re hiring a Senior Software Engineer to team with our Machine Learning Engineers and Researchers to build software that powers Lila’s ML workflows and research tooling. You will be on a team of software engineers that work alongside machine learning experts to develop, support, and maintain Lila’s ML libraries and tools.

What You’ll Be Building

• Design and build high-performance, secure, and well-documented Machine Learning libraries that implement the algorithms designed by machine learning researchers and engineers.
• CI/CD pipelines and integration tests for ML workflows.
• Architect repository designs to follow consistent standards.
• Support debugging, logging, and maintenance for Ray-based compute environments.
• Data ingestion pipelines linking lab data to ML teams.

What You’ll Need to Succeed

• Minimum of 8 years of experience writing software in a commercial setting in Go or Python.
• Experience implementing scalable software solutions.
• Experience with MLOps systems, GitOps (ArgoCD, Github Actions)
• Familiarity with orchestration frameworks (Ray, Argo, Airflow).
• Proficiency in Containerization, Kubernetes and infrastructure-as-code tools.
• Acute listening skills and patience to deeply understand complex problems and algorithms.
• Excellent problem-solving skills and team-first mentality.
• Energetic self-starter and independent thinker with strong attention to detail.
• Eager to work with highly skilled and dynamic teams in a fast-paced, entrepreneurial, and technical setting.

Bonus Points For

• Proficiency with monitoring and logging tools (e.g., Prometheus, Grafana)
• Research engineering or scientific software experience.

Your Impact at LILA

We are seeking a Staff Software Engineer - AI Lab Execution System to join our software group and help build the next generation AI-driven scientific platform. In this role, you will design, build, and optimize intelligent, data-driven applications front-end. You will focus on developing UI, services, high-performance APIs, databases, and ensuring the reliability of services that integrate advanced AI frameworks with complex scientific analytics and laboratory workflows.

You’ll work closely with ML researchers, platform engineers, and scientists to develop systems that can handle diverse workloads and scale seamlessly, including structured SQL database, data lake houses, and vector databases. This is an opportunity to apply your deep front-end and backend expertise to a cutting-edge AI platform with real scientific impact. If you are passionate about building performant, and elegant systems, we would love to hear from you!

What You'll Be Building

• Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 4-6 years of engineering experience building and deploying large-scale systems in production. You must be strong in either front-end or backend or data modeling and design.
• Typescript, React and Python Expertise: Strong experience with React and Typescript is required.
• Expertise in Databases: Strong experience with SQL, NoSQL, and emerging database technologies (e.g., Vector DBs); proven track record in schema design, indexing, and query optimization.
• API Development: Proven ability to design and scale RESTful or GraphQL APIs with a focus on reliability and performance.
• Hands on experience using AI coding assistants to drive productivity is required.
• Scientific or Data-Intensive Domains: Experience working with life sciences, material sciences, or other research-heavy fields.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.

Bonus Points For

• Cloud & DevOps Knowledge: Hands-on experience with AWS, GCP, or Azure; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Orchestration Systems: Experience with orchestration tools (Flyte, Temporal, Airflow, Prefect, etc.).

Your Impact at LILA

The Staff/Principal DevOps Engineer will drive the design, implementation, and optimization of our infrastructure and delivery platforms. This role bridges platform engineering, site reliability, and DevOps practices, building scalable, automated systems that enable fast, reliable software delivery across cloud and Kubernetes environments. You will collaborate with software engineers, lab scientists, and ML engineers to build infrastructure that powers automated scientific analysis, experiment orchestration, and more.

What You'll Be Building

• Build Kubernetes-based infrastructure supporting scientific services, ML pipelines, and platform workloads; including production hardening, RBAC, network policies, and Pod Security Standards
• CI/CD pipelines with GitHub Actions/GitLab CI implementing best practices: build attestations, SBOM generation, dependency scanning, and container image hardening
• Infrastructure-as-code with Terraform and Helm; policy-as-code guardrails (OPA/Kyverno/Checkov) with drift detection
• AWS cloud infrastructure: EKS clusters, IAM least privilege, VPC/PrivateLink networking, KMS/Secrets Manager, ECR, S3, and centralized logging/monitoring
• Platform tooling to streamline deployment, observability, and developer workflows, enabling self-service with secure defaults
• Reliability engineering: SLOs/SLIs, incident response, capacity planning, and performance optimization throughout the stack
• Software supply chain practices: artifact signing, registry governance and vulnerability management
• QA and testing infrastructure: static analysis and code quality gate enforcement in CI pipelines, automated end-to-end and browser-based regression test suites, ephemeral test environments for PR-based validation, and pre-merge quality checks
• Automation and tooling in Python or Go to improve infrastructure operations and integrate telemetry with observability platforms

What You’ll Need to Succeed

• Expertise in DevOps, SRE, or Platform Engineering in large scale cloud environments
• Expertise in deploying to cloud environments (AWS, GCP, etc) using infrastructure-as-code (Terraform, Helm) and containerization
• Deep experience with CI/CD systems (GitHub Actions, GitLab CI, or Jenkins) and GitOps practices
• Strong proficiency in Python/scripting languages for automation and tooling
• Strong understanding of Kubernetes operations: deployments, networking, storage, observability, and troubleshooting

Bonus Points For

• Experience with GitOps tools (ArgoCD, Flux)
• SRE practices: observability platforms, chaos engineering, incident management
• Securing ML/AI pipelines (model registries, training clusters, inference gateways)
• Experience in regulated/audit-heavy environments (SOC 2, ISO 27001)
• Supply chain security maturity: SBOMs, image signing, SLSA concepts
• Administering static analysis platforms (custom quality profiles, security hotspot triage) and scaling browser-based test suites across parallel CI environments
• Prior startup/high-growth experience balancing velocity with reliability

Your Impact at LILA

Join us in shaping the future of science! We are seeking a software engineer with a background in life sciences to join our data science team, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. This role spans web services and data engineering, with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

What You'll Be Building

• Participate in the entire software development life cycle, focusing on designing, implementing, and maintaining software services.
• Develop reusable code and libraries to improve efficiency and scalability.
• Align development with strategic goals, ensuring software supports broader organizational needs.
• Manage git repositories, team Jira board and Notion Hub, promote best practices, assist lab scientists with use of new tools, and foster a collaborative development culture.
• Work directly with scientists to identify gaps and unmet needs, develop tailored software solutions for data management, LIMS functionality, and data automation
• Support infrastructure as code and design efficient deployment strategies.
• Write clear, concise documentation for both engineers and end users.

What You’ll Need to Succeed

• Minimum of 2 years of experience writing software in a commercial setting.
• High-level proficiency in Python.
• Strong understanding of git best practices.
• Acute listening skills and patience to deeply understand user challenges.
• Experience implementing scalable software solutions.
• Excellent problem-solving skills and team-first mentality.
• Strong communication skills to effectively collaborate with team members and stakeholders.
• Energetic self-starter and independent thinker, with strong attention to detail.
• Eager to work with highly skilled and dynamic teams in a fast-paced, entrepreneurial, and technical setting.

Bonus Points For

• Background in biological sciences
• Familiarity with data science and ML libraries (pandas, numpy, scipy).
• Knowledge of modern developer tools (pydantic, pyright, uv).
• Understanding of Kubernetes, ArgoCD, and GitHub Actions.
• Familiarity with AWS fundamentals (e.g., RDS, EC2, S3, EKS).

Who We Are

Flagship Pioneering is a biotechnology company that invents and builds platform companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health and sustainability exponentially accelerate scientific progress in areas ranging from cancer detection and treatment to nature-positive agriculture.  

What sets Flagship apart is our ability to advance biotechnology by uniting life science innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet.  

Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. 

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies.

About the Role

The Information Security team has strong detection and response capability and a maturing compliance program. This is a greenfield opportunity to build Flagship’s cloud security and application security engineering practice in earnest — with the CISO and Director of Security Engineering as your strategic partners and a well-resourced program behind you. You’ll define how cloud posture management, SSDLC security, and cloud-side DLP get done at Flagship — in deep partnership with the Infrastructure & Operations team, who are your primary counterparts for cloud architecture, network, and endpoint infrastructure. What makes this role distinctive is the expectation that you’ll build AI-augmented workflows from the start — using LLMs and agentic tooling to handle the routine 80% so your expertise stays focused on the 20% that actually requires human judgment. If you want to own a practice area rather than execute someone else’s playbook, this is that role. You'll own the technical execution of cloud security and AppSec across Flagship and its portfolio, working directly with engineering teams to embed security into their pipelines, not just review them after the fact.

What You'll Own

• Cloud security posture management: own remediation execution against Wiz findings in close partnership with Infrastructure & Operations — building shared remediation playbooks, coordinating finding resolution across AWS environments, and ensuring security controls are implemented consistently with I&O’s infrastructure standards
• CI/CD and SSDLC security: design and implement security guardrails in engineering pipelines — SAST, secrets scanning, IaC security, container scanning — working directly with portfolio engineering teams, and building AI-powered pipeline security automation (e.g., LLM-assisted code review, automated fix suggestions for SAST findings) that reduces developer friction and scales security coverage beyond what manual review allows
• Cloud-side DLP enforcement: build and operationalize data loss prevention controls at the cloud and application layer, not just policy definition
• Cloud identity and access: own technical execution on Entra/Azure AD conditional access, BYOD policy enforcement, and cloud identity governance in partnership with Infrastructure & Operations, who manage the underlying directory and endpoint infrastructure
• Detection engineering (cloud layer): write and tune cloud-side detection rules and contribute to alert fidelity improvements in partnership with the SOC
• AI platform security: contribute to security architecture reviews and guardrail design for AI-powered portfolio products, including Bedrock and EKS-based platforms
• Serve as the embedded security engineering partner for portfolio company engineering teams — not a reviewer at the end of the process, but a collaborator throughout it
• Design and maintain AI-augmented workflows across all functional areas you own — using LLMs, agentic tooling, and automation to multiply your own capacity. You'll be expected to treat AI as a core part of your engineering toolkit, not an experiment: building prompt-driven triage pipelines, automating remediation drafting, and continuously identifying where human judgment is the bottleneck versus where it's being wasted on pattern-matchable work.

What We're Looking For

• 5+ years in cloud security, application security, or a closely related security engineering discipline
• Deep hands-on experience with AWS security services (Security Hub, GuardDuty, IAM, SCPs, CloudTrail) and cloud posture tooling — Wiz experience strongly preferred
• Practical AppSec experience: you've integrated SAST/DAST/SCA tooling into CI/CD pipelines and worked directly with developers to resolve findings, not just filed tickets
• Experience with cloud identity platforms — Entra ID / Azure AD, including conditional access policy design and enforcement
• Ability to write infrastructure-as-code and scripting to automate security controls (Python, Terraform, or equivalent), including comfort working with LLM APIs, prompt engineering, and agentic orchestration frameworks
• Demonstrated experience building AI-augmented security workflows — you've used LLMs, agentic frameworks, or AI-assisted tooling to automate security tasks at scale, not just experimented with ChatGPT. You should be able to articulate which security problems are well-suited to AI automation and which aren't.
• Strong enough communication skills to be credible with engineering leadership and portfolio company CTOs — you’ll be in technical design reviews, not just security reviews Proven ability to build trusted working relationships with Infrastructure & Operations teams — you approach I&O as a partner, not a gatekeeper, and can influence security outcomes through collaboration rather than mandate
• Comfort operating as a self-directed practitioner in a lean team; this role requires you to set your own execution priorities within a defined strategic direction

Nice to Have

• Experience securing ML/AI platforms — Bedrock, SageMaker, or comparable environments
• AWS Security Specialty, GWEB, OSCP, or equivalent certification
• Experience in a portfolio company or multi-entity security model
• Familiarity with HIPAA technical safeguard requirements and PHI data flows in cloud environments
• Experience designing or operating agentic AI workflows for security operations
• Container and Kubernetes security experience (EKS, image scanning, network policy)

Why This Role

This is a net-new capability role on a small team — you won't be executing someone else's existing playbook, you'll be building the cloud and AppSec program from a solid foundation. You’ll work directly with the CISO and collaborate closely with the Director of Security Engineering. Flagship's portfolio spans some of the most technically ambitious biology and AI work happening anywhere, and the security work reflects that complexity. If you want a role where the scope is real, the autonomy is genuine, and you have the freedom to build an AI-augmented security practice — this is it.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. 

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship. 

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto. 

#LI-NM1 

The salary range for this role is $148,000 - $203,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Flagship Pioneering currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Flagship Pioneering's good faith estimate as of the date of publication and may be modified in the future.

CMT is looking for a Principal Backend Software Engineer to produce scalable software solutions to reliably collect and manage data from sensors on smartphones and connected devices in vehicles. In this role, you will design architecture and backend infrastructure, and build features and applications that meet the needs of our customers. If you’re interested in using your skills to make the world's roads and drivers safer, we’d like to meet you. The person in this role will own the architecture and evolution of the backend systems that power DriveWell Fusion. You will design and scale high-throughput data pipelines, REST APIs, and real-time event processing systems that handle millions of device connections daily. You will partner with ML and Data Science teams to build the compute and data infrastructure that supports model training, feature engineering, and large-scale inference — including GPU-accelerated workloads. You will drive infrastructure-as-code practices, CI/CD reliability, and system observability to ensure our platform remains performant and resilient as we grow. As a technical leader, you will mentor engineers, set technical direction, and collaborate with product and engineering stakeholders to deliver solutions that keep tens of millions of drivers safe. 

CMT has helped protect over 65 million drivers and prevent over 126,000 crashes worldwide. We build AI to solve some of the most difficult challenges in mobility — understanding and reducing risk, detecting crashes, and getting people life-saving help. The problems are hard. The impact is real. No matter your role, your work will matter at CMT.

Responsibilities: 

• Participate throughout the planning process, collaborating with product managers, data scientists, and fellow engineers to balance technical feasibility with customer needs 
• Use independent judgment and discretion to implement and enhance solutions for telematics insights enabled by our processing pipelines 
• Identify and measure key production performance metrics, ensuring scalability and efficiency
• Design, implement, and maintain automated tests for telematics solutions, ensuring safe delivery of features and fixes 
• Ensure high bar for quality within our sphere of influence 
• Provide expert guidance on cloud software architecture 
• Keep the codebase healthy amidst increasing complexity 
• Mentor junior engineers as needed 
• Complete any additional tasks as they arise 

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Computer Science, Engineering, or related field 
• 7+ years of relevant professional experience 
• Proven experience with development at scale 
• Fluency in at least one programming language with ability to learn Python, Go, C++
• Experience with continuous deployment, and test-driven development (TDD) 
• Experience with relational database (RDBMS) schema design 
• Comfortable with AWS or similar services
• EC2, S3, Lambda, SNS, SQS, RDS (Postgres), Dynamo 
• Terraform, Terragrunt 
• Knowledgeable of containerization technologies (specifically Docker) 
• Ability to work independently when needed and to learn quickly

Nice to Haves: 

• Experience with large-scale cloud compute for ML inference, including GPU-accelerated infrastructure (e.g., EC2 GPU instances, SageMaker, EKS with GPU scheduling), GPU vs CPU workload allocation, model serving at scale, and trade-offs between batch and real-time inference 
• Experience building and operating data pipelines (ETL/ELT) at scale, and designing the data infrastructure that ML/Data Science teams rely on for feature engineering, model training, and production inference 
• Hands-on experience designing and operating high-throughput backend systems handling millions of API requests and device connections daily, including real-time data ingestion and event-driven architectures (message queues, streaming platforms) 
• Hands-on experience with containerization (Docker), container orchestration (AWS ECS or Kubernetes), and infrastructure-as-code using Terraform for managing cloud environments at scale
• Proficiency with observability and monitoring (Datadog, CloudWatch) including designing monitors, alerts, and SLOs 
• Strong knowledge in web security, session management, and experience with network diagnostics and analytics tools
• Experience using AI-assisted development tools (e.g., Claude Code, Cursor) as part of daily engineering workflows

Compensation and Benefits: 

• Fair and competitive salary based on skills and experience, and annual performance bonus 
• Equity may be awarded in the form of Restricted Stock Units (RSUs) 
• Medical, Dental, Vision and Life Insurance, matching 401k, short-term & long-term disability and parental leave 
• Unlimited Paid Time Off including vacation, sick days & public holidays 
• Flexible scheduling and work from home policy depending on role and responsibilities

Base Salary Range

• The base salary range for this position is: $167,200 to $209,000. This range is specifically for Cambridge, MA

Additional Perks:

• Work on a mission with real impact: crashes prevented, injuries avoided, lives protected around the world
• Join an industry leader — 65 million drivers protected, powering 140+ programs across 25 countries
• Be part of the team inventing the future of mobility and road safety
• Move fast, own outcomes, do work that matters
• High ownership, small teams, and direct access to leadership — no layers between your work and its impact
• Unlimited PTO, flexible scheduling, competitive salary, annual performance bonus, RSUs, and full benefits including medical, dental, vision, and 401k match
• Summer Fridays
• Join one of our employee resource groups: Black, AAPI, LGBTQIA+, Women, Book Club, and Health & Wellness
• Comprehensive wellness, education, and employee assistance programs

Commitment to Diversity and Inclusion:

At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. 

We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. 

We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

About Cambridge Mobile Telematics:

Cambridge Mobile Telematics (CMT) is the world’s largest telematics and AI company for safer mobility. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, proactively identifies and reduces driving risk, leading to fewer crashes and injuries. To date, CMT’s technology has helped prevent over 126,000 crashes worldwide. CMT enables partners to measure risk, detect crashes, provide life-saving assistance, and streamline claims. Headquartered in Cambridge, MA, CMT operates globally with offices in Budapest, Hungary; Chennai, India; Seattle, Washington; Tokyo, Japan; and Zagreb, Croatia. Learn more at www.cmt.ai.

COMPANY DESCRIPTION

Extuitive is a Flagship Pioneering–backed startup reimagining product innovation for the AI era. Our mission is to empower entrepreneurs and direct-to-consumer (D2C) brands with AI-driven tools that simplify, accelerate, and scale the launch of new products. Based in Cambridge, MA, we operate like a special ops unit—fast-moving, data-driven, and relentlessly focused on impact.

THE ROLE

As a Principal Backend Engineer, you’ll be a technical leader responsible for architecting, building, and scaling the core backend systems that power our platform. You’ll drive the design of high-throughput services, resilient data pipelines, and integrations with mission-critical third-party providers. Working closely with product managers, designers, and engineering leadership, you’ll translate complex requirements into robust, elegant systems that support rapid growth. You’ll mentor engineers, influence long-term technical strategy, and help evolve our platform architecture to maintain security and reliability as we scale.

KEY RESPONSIBILITIES

• Own Core Backend Systems – Design, build, and maintain scalable services, APIs, and platform infrastructure. Ensure reliability, observability, and maintainability.
• Drive Large-Scale Data Pipelines – Architect and operate high-volume, resilient data pipelines for ingestion, transformation, and analytics.
• Lead Third-Party Integrations – Build and maintain integrations with external vendors, ensuring reliability, observability, and long-term maintainability.
• Influence Architecture & Best Practices – Shape backend architecture, coding standards, testing frameworks, CI/CD pipelines, and operational excellence.
• Mentor & Lead Engineers – Provide guidance on system design, debugging at scale, and engineering practices.
• Wear Multiple Hats – Support DevOps, troubleshooting, or other platform needs when necessary.

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• 8+ years of backend engineering experience.
• Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience.
• Strong expertise in backend languages and frameworks (Node.js/TypeScript, Go, Python, or similar).
• Experience designing scalable distributed systems, microservices, and event-driven architectures.
• Deep experience with third-party integrations, REST/GraphQL APIs, webhooks, and rate-limited services.
• Proficiency with SQL/NoSQL databases, data pipelines, and performance optimization.
• Familiarity with cloud platforms (AWS, GCP) and containerized/deployed systems (Docker, Kubernetes).
• Strong testing, CI/CD, and observability practices.
• Comfortable working in a fast-paced, evolving environment with minimal oversight.

Nice to Have 

• Experience building and shipping features quickly in early-stage startups.
• Exposure to multiple backend domains (analytics, payments, notifications, workflow orchestration).
• Hands-on experience with serverless or edge architectures for rapid iteration.
• Familiarity with low-friction integrations with third-party tools and SaaS platforms.
• Track record of scaling systems from small MVPs to production-ready services.
• Comfort with ambiguity and making trade-offs between speed, quality, and maintainability.

ABOUT FLAGSHIP PIONEERING:

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  

Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact.

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

Recruitment & Staffing Agencies: Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

The salary range for this role is $152,000 - $209,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Extuitive, Inc. currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Extuitive, Inc.'s good faith estimate as of the date of publication and may be modified in the future.

We are hiring a Principal Machine Learning Engineer to work on cutting-edge R&D and translating research into customer-centric solutions.   

As innovators in speech technology, our mission is to Understand Every Voice—a vision that has propelled us to be world leaders of Voice AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Principal Machine Learning Engineer to accelerate our efforts towards exceptional speech solutions. 

Our Modelling Team trains diverse models, including large self-supervised ones, supporting Speechmatics towards being the most accurate speech recognition system globally. It also ensures their deployment into production, working with the latest developments in ML, but also with the best engineering practices for software engineering and model serving. 

This is a hands-on, technical leadership role with high ownership.  You will develop and deploy advanced speech systems that power our products as well as co-define the technical vision for ML, drive innovation, and mentor engineering teams. Your work will span the entire codebase.    

What You’ll Do:

• Develop and deploy ML models, translating research into scalable, maintainable code and services 
• Optimise ML models for speed, accuracy, and cost efficiency 
• Evaluate and integrate cutting-edge approaches into our ML stack
• Identify and solve complex ML problems across the organisation
• Define and enforce best practices for code quality, model lifecycle management, etc.
• Mentor engineers and foster a culture of technical excellence and innovation
• Co-define the long-term technical vision 

What We’re Looking For:

• Deep understanding of the modern Machine Learning stack, for example:
  • Knowledge of contemporary transformer architectures (e.g., GQA, KV-caching) and best practices
  • Expertise in distributed training techniques
  • Familiarity with optimisation strategies for model inference (e.g., dynamic batching, flash attention, speculative decoding)
• Proven track record of developing and deploying models at scale
• Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms
• Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes)

  With preferred backgrounds covering some of the following:

• Experience with speech-to-text or text-to-speech 
• Contributions to open-source projects or published research in top-tier conferences

About Philo

Philo is building the future of television. Our product lets you watch your favorite shows on all the devices you care about, with seamless playback, insightful discovery, and effortless sharing. In short, we’re building the TV experience that we’ve always wanted for ourselves.

We’re a company that puts people first — both our subscribers and our team. At Philo, our philosophy is to empower our colleagues to do their best work while supporting each other in pursuing shared goals. We value pragmatism, pride in our work, and passion. We believe in having transparency and openness across all parts of the company.

We are committed to diversity and inclusion as we grow the Philo team and shape the future of TV. We believe that a diverse set of voices and perspectives on our team enables us to innovate faster and create the best experience for our subscribers.

Philo is headquartered in San Francisco, with offices in New York City and Cambridge, MA. Our leadership team includes alums from HBO, Tubi, and Meraki, and is backed by NEA and industry partners like Warner Brothers Discovery, Viacom, AMC, and A&E.

Lead Backend Software Engineer (Product)

Philo aims to connect customers with their favorite shows, help them discover new favorites, and get them seamlessly into the video player watching their next shows. The Product API team is central to this mission and powers virtually every non-media interaction in our application delivering a personalized experience for millions of users across web, mobile, and connected TV platforms.

The team builds out the Philo show catalog and exposes it via search, ML powered recommendation, and platform integration like search on Roku, FireTV, and tvOS. They provide a robust API to clients platforms to access this catalog along with features needed for a streaming service like saving shows, sending notifications, and running experiments. They do this all while load testing and scaling the system to millions of users and considering security and privacy. A challenge for the team is to support many different clients and the team has built out frameworks, infrastructure, and APIs to enable this. For example, building out a framework on top of GraphQL to dynamically change the home page instantly and across all platforms without any client modification allowing for content curation, user personalization, and all types of home page experimentation.

Engineering leads at Philo lead by example, and are expected to ship features, triage bugs, manage releases, and generally advocate for quality throughout the codebase. We are seeking an enthusiastic, experienced backend engineer with a deep technical background building scalable APIs, services, and platform infrastructure. You will contribute to the technical vision and roadmap for Product API, drive architecture and reliability with strong observability, coordinate cross-team delivery to unblock new user experiences, and ensure partner integrations land smoothly. You'll model best practices to the team, unblock your teammates when they are stuck, and help ensure platform stability and clarity of contracts as the team delivers multi-quarter outcomes.

Responsibilities

• Provide technical leadership to members of the Product API team, including input on system architecture and design tradeoffs, as well as coaching other members of the team and mentoring new hires.
• Collaborate with product and client engineering teams to design and deliver GraphQL APIs that enable rich, performant user experiences while maintaining clean separation of concerns and optimal client-server interactions.
• Own and evolve critical product subsystems including recommendations, catalog, search, in-app notifications, user preferences, viewing history, collections, experiments, and feature flags.
• Build and maintain proxy and augmentation layers that integrate domain services from across the organization (such as video infrastructure, recommendations systems, and search) into a cohesive, unified API.
• Drive continuous improvements to the reliability, performance, scalability, and maintainability of Philo's product API infrastructure, ensuring sub-second response times and high availability across all endpoints.
• Collaborate with data science and product analytics teams to instrument the API layer for experimentation, A/B testing, and feature rollouts, enabling data-driven product decisions.
• Build and enhance observability tools to proactively monitor API performance, identify bottlenecks, debug issues, and ensure optimal cache utilization across the system.
• Work with infrastructure teams to optimize database queries, implement effective caching strategies, and ensure DataServer scales efficiently as Philo's user base grows.

Qualifications

• 8+ years of software development experience.
• 2+ years of experience mentoring and providing technical guidance to other engineers (bonus points for experience or interest in managing engineering teams).
• Strong experience designing and implementing GraphQL APIs at scale (bonus points for experience with complex schema design, query optimization, and federation patterns).
• Proven track record of building highly efficient and highly available backend services using NodeJS, Ruby, Golang, Python, or similar programming languages.
• Experience operating in cloud computing environments using modern software deployment technologies (e.g. Docker, Kubernetes, AWS).
• Deep understanding of API design principles, RESTful and GraphQL patterns, caching strategies, and performance optimization techniques.
• Experience working with large amounts of data and making data-based decisions to prioritize projects, including familiarity with relational and non-relational databases and modern data warehousing and querying with SQL.
• Strong systems thinking with the ability to design cohesive API abstractions that cleanly separate concerns while enabling flexibility for diverse client needs.
• Experience building proxy and aggregation layers that integrate multiple backend services into unified APIs.
• Familiarity with experimentation frameworks, feature flag systems, and A/B testing infrastructure.
• Experience and aptitude for collaborating and communicating with internal stakeholders across product, design, client platform engineering, and data science teams.
• Understanding of video streaming product ecosystems and the unique challenges of building APIs for multi-platform applications (web, mobile, TV).
• Expertise in either product-facing API development or machine learning systems and model serving infrastructure.

We are language agnostic, but most of our backend code is written in Golang, NodeJS and Ruby, with some C++ and Python. Our services run on Kubernetes, and we practice continuous deployment across all of our systems.

More about Philo

At Philo, we’re a company that puts people first—both our subscribers and our team. We empower our colleagues to do their best work while supporting one another in pursuing shared goals. We value pragmatism, pride in our work, and passion, with transparency and openness as fundamental parts of our culture.

We’re committed to diversity, equity, inclusion, and accessibility as we grow the Philo team and shape the future of TV. We believe that a diverse range of voices and perspectives enables us to innovate faster and create the best experiences for our subscribers. Philo is proud to be an Equal Opportunity Employer. We’re committed to supporting every candidate and employee. If you need an accommodation at any stage of the process, please email recruiting@philo.com and we’ll work with you to meet your needs.

Philo offers 70+ top-rated networks, including AMC, BET, CMT, Comedy Central, Discovery Channel, Food Network, Hallmark Channel, HGTV, HISTORY, Investigation Discovery, Lifetime, MTV, Nickelodeon, OWN, VH1, We TV, and more. It also includes all the groundbreaking originals and blockbuster movies available with AMC+ and access to HBO Max Basic With Ads and discovery+. Our service also includes 100+ free channels and premium add-ons like STARZ and MGM+.

Our extensive library boasts over 85,000 titles, and our unlimited DVR allows users to save their favorite shows and movies for up to a year, skipping ads for a seamless viewing experience. Stream on up to three devices simultaneously, whether on your phone, tablet, laptop, or TV using Roku, Apple TV, Fire TV, Samsung TV, Android TV, Vizio TV, or Chromecast.

Join us at Philo and be part of a team that's shaping the future of TV!

Projected Start Date: ASAP
Status: Full-time
Location: San Francisco, CA, Brooklyn, NY, Cambridge, MA, or remote within the U.S.
Compensation: Includes annual salary, company stock options, and health benefits. Salary is determined by experience and location:

• San Francisco, New York City: $200K - $235K
• Boston, DC Metro, Los Angeles, Seattle: $190K - $225K
• Denver, Atlanta, Austin, Las Vegas, Sacramento, Chicago: $180K - $215K
• Texas, Florida: $170K - $205K

We value a diverse and inclusive workplace and we welcome people of different backgrounds, experiences, skills, and perspectives. Philo is an equal opportunity employer. We believe that everyone does their best work when they are supported by each other and the company, and we offer a generous set of benefits to make sure the Philo team is happy and healthy. Here is a sampling of the benefits we offer our team:

• Full health, dental and vision coverage for you and your family
• 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay)
• Flexible working hours
• Up to 20 weeks of fully paid parental leave
• Unlimited paid time off for vacation and sick leave
• $2,000 annual vacation bonus (we pay you to take a two week vacation)
• $5,250 annually for professional development and educational assistance
• $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter)
• $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco)
• Free Gympass subscription — an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps
• Dog-friendly office
• And much more!

For California Residents: Philo’s CCPA Notice at Collection – Employees, Applicants, Owners, Directors, Officers and Contractors

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

BrightSign, the global market leader in digital signage media players, seeks an experienced software test engineer to join their embedded development team.  In this role you will have primary ownership of the CI/CD pipeline and associated test systems for BrightSign’s embedded products, predominantly but not exclusively Linux-based media players.

Responsibilities
•    Develop and maintain automated test infrastructure, both hardware and software
•    Design, architect and develop improvements to build infrastructure for performance, maintainability and cost optimisations
•    Monitor and report on quality metrics derived from local testing and field reports
•    Assist software development teams in resolving issues with build, test or deployment
•    Work with product management and other internal stakeholders to prioritise activities appropriately

 Qualifications and Skills
•    Degree in engineering, computer science or related discipline
•    Minimum 5 years industry experience in a professional software environment
•    Familiarity with Yocto/OpenEmbedded
•    Experience with Python, JavaScript and shell scripting
•    Experience of Linux systems (as a user, not necessarily a developer or administrator)
•    Excellent communication skills; written and verbal
•    Attention to detail
•    Ability to work independently with minimal supervision

Desirable
•    Previous experience of digital multimedia or networked systems
•    Experience with Kubernetes, AWS and similar cloud technologies
•    Familiarity with Gerrit, GitHub and/or other code review systems