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 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

We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE’s AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE’s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  

• Use MLOps tools for efficient experiment tracking, data management, and reproducibility 

• Write robust, efficient, and maintainable code 

• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 

• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 

• US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance 

• Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 

• Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 

• Proven experience testing and validating the performance of AI technologies in real-world applications 

• Proficiency in Python  

• Experience with cloud platforms (AWS and Azure)  

• Experience with Docker 

• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 

• Exceptional communication skills and the ability to work well with customers 

• Understanding of Department of Defense requirements and standards is a plus 

We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE’s AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE’s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  

• Use MLOps tools for efficient experiment tracking, data management, and reproducibility 

• Write robust, efficient, and maintainable code 

• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 

• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 

• US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance 

• Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 

• Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 

• Proven experience testing and validating the performance of AI technologies in real-world applications 

• Proficiency in Python  

• Experience with cloud platforms (AWS and Azure)  

• Experience with Docker 

• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 

• Exceptional communication skills and the ability to work well with customers 

• Understanding of Department of Defense requirements and standards is a plus 

We are seeking a Machine Learning Engineer to join our team at MORSE.  You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms.  MORSE’s AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE’s current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 

• Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  

• Use MLOps tools for efficient experiment tracking, data management, and reproducibility 

• Write robust, efficient, and maintainable code 

• Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 

• Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 

• US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance 

• Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 

• Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 

• Proven experience testing and validating the performance of AI technologies in real-world applications 

• Proficiency in Python  

• Experience with cloud platforms (AWS and Azure)  

• Experience with Docker 

• Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 

• Exceptional communication skills and the ability to work well with customers 

• Understanding of Department of Defense requirements and standards is a plus 

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’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

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).

We are embarking on a transformative journey with DriveWell Atlas, a groundbreaking initiative to build a family of novel AIs on telematics data. As a Principal Machine Learning Engineer on the DriveWell Atlas team, you will be at the forefront of developing these next-generation AIs. You will lead innovative projects focused on designing, pre-training, fine-tuning, and deploying these AIs. Your work will directly contribute to enhancing our capabilities in risk assessment, driver engagement, and crash and claims processing. This role requires a deep understanding of modern AI methods, machine learning, physics-informed modeling, and experience with sensor data. We are not tweaking existing models for marginal gain. You will have an opportunity to build a first-of-its-kind LLM from petabyte-scale data. 

CMT is looking for a Principal Machine Learning Engineer, Foundation Models to help us change the world. 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: 

• Use independent judgment and discretion to lead the design, pre-training, fine-tuning, and deployment of novel foundation models for vehicle telematics 
• Develop and implement novel algorithms for modeling both automotive physics and human driving behavior 
• Pioneer advanced self-supervised learning techniques, including the design and implementation of innovative tasks tailored to multi-modal telematics sensor data to learn rich representations of movement and driver behavior 
• Develop models robust to noise, missing data, and diverse operating conditions typical of real-world mobile sensor and IoT datasets 
• Build and manage scalable training and inference pipelines using tools like Ray, PyTorch DDP, Horovod, or similar frameworks 
• Integrate these AIs into production systems while ensuring high performance and reliability
• Optimize these AIs for efficient deployment on various platforms, including cloud and edge/mobile devices 
• Collaborate closely with engineering, product, and research teams to translate cutting-edge research into impactful products and features for the DriveWell Atlas platform 
• Mentor junior scientists and contribute to the broader AI/ML strategy at CMT 
• Stay abreast of the latest AI advancements, evaluating and adopting emerging technologies and methodologies relevant to telematics 
• Contribute to efforts in AI explainability and interpretability 
• Complete any tasks as they arise

Qualifications: 

• Bachelor’s degree or equivalent years of experience and/or certification in Artificial Intelligence, Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, or a related field 
• 7+ years of professional experience in AI/ML 
• 3+ years of hands-on experience developing and deploying foundation models, with a strong portfolio in generative AI for sequential or spatio-temporal data 
• Strong, hands-on experience in building and training time-series transformer architectures for complex sensor fusion and behavioral modeling tasks is required 
• Deep expertise in designing pretraining tasks for self-supervised learning on noisy, real-world sensor data 
• Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, scikit-learn)
• Extensive experience with deep learning frameworks such as PyTorch (preferred) or TensorFlow for large-scale model training and deployment 
• Solid understanding and practical experience with distributed training techniques and efficient training methodologies for large models 
• Experience building and maintaining large-scale data processing pipelines and machine learning infrastructure using tools like Spark, Airflow, Docker, and cloud platforms (e.g., AWS, GCP, Azure)
• Excellent problem-solving skills and the ability to translate complex business problems into tractable AI-based solutions 
• Strong verbal/written communication and collaboration skills, with the ability to effectively convey complex technical concepts to diverse audiences 
• Product-focused thinking with a proven ability to deliver impactful AI solutions

Nice to Haves: 

• PhD or Master's degree preferred 
• Experience with MLOps practices and tools for managing the lifecycle of machine learning models
• Publications in top-tier AI/ML conferences or journals 
• Familiarity with techniques for model interpretability and explainability (XAI) 
• Awareness of ethical AI principles, bias detection, and mitigation strategies in machine learning models, including experience with or understanding of model guardrails

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: $177,000 to $221,300. 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.

About Dimagi

Dimagi is an award-winning social enterprise and a certified B-corp and Benefit Corporation. We build software solutions and provide technology consulting services to improve the quality of essential services for underserved populations. Our open-source technology platform, CommCare, is the world’s most widely-used and researched mobile data collection platform for frontline workers. Our choice to be a certified B-Corp and to legally incorporate as a Benefit Corporation sends a clear signal to our partners, our team members, and our communities that we not only believe but also take action in using business as a force for good. This approach combines our passion and commitment to tackle complex health and social inequities and work towards a brighter future for all.

About the Position

Dimagi is looking for a Data Engineer II to join our US Solutions Division. This position will be affiliated with our Cambridge, MA office but is open to remote employment within the United States. This is a 12-month fixed-term position with the possibility of renewal based on business requirements and mutual interest. 

The Data Engineer II will be part of Dimagi’s US Solutions Division Data & Analytics team, a group of engineers and data specialists responsible for building, maintaining, and evolving Dimagi’s Data Platform in support of current and future project work. The primary technologies used by the current data platform are Snowflake, Tableau, and various AWS cloud tools. In this role, you will contribute hands-on to the design, implementation, and operation of data pipelines, warehouse transformations, data visualizations, and supporting infrastructure, while working closely with technical leadership to ensure platform reliability, scalability, and alignment with business needs. The data systems you help build and maintain will directly support public health and human services programs, enabling frontline teams and government partners to deliver care and services more effectively.

This position is well suited for someone who enjoys hands-on technical work in a small, collaborative environment. As a member of a lean team, you will be expected to work across functional areas, adapt quickly to new problem spaces, and contribute meaningfully to data systems that support real-world service delivery and decision-making.  This role assumes comfort using AI-assisted tools to support analysis, documentation, troubleshooting, and learning in a complex technical environment.

Responsibilities 

• Contribute to the technical integrity and evolution of the Data Platform tech stack, working closely with other Data Engineers, the Director of Technology, and the USS Tech Lead.
• Design and implement core features and enhancements within the Data Platform, including contributing to technical specifications, conducting targeted technical research, and translating requirements into production-ready solutions.
• Responsible for executing and maintaining DevOps workflows supporting the Data Platform, including performance monitoring, platform upgrades, deployment frameworks, and operational improvements, with guidance and mentorship from more senior Data Engineers as needed.
• Use AI-assisted tools thoughtfully to accelerate development, debugging, documentation, and operational analysis, while understanding and validating outputs to ensure correctness, reliability, and security.
• Build and maintain robust data extraction, loading, and transformation processes for both Dimagi managed (i.e. CommCare) and external data sources, enabling efficient, reliable data pipelines and their long-term development and operation using both SQL and Python scripting.
• Design and develop data warehouse transformations, using SQL-based approaches and supplementary tools such as dbt.
• Collaborate with internal teams and external partners on the design and implementation of enterprise data architectures based on industry standards and partner specific analytics needs.
• Conduct ad hoc analyses and support the development of business intelligence outputs, including dashboards and visualizations using Tableau and other tools.

The ideal candidate will have some or all of the following experience:

• 2–5 years of experience in data engineering or a similar technical role, with a proven track record of designing and evolving scalable data systems.
• Experience building maintainable, long-term technical solutions using software development best practices (version control, testing, and iterative development).
• Hands-on expertise in building and managing production-grade pipelines using ETL/ELT tools (e.g., dbt, Airflow, Prefect, Fivetran, or Talend).
• Strong proficiency with cloud-based data platforms (AWS, Snowflake, etc.) and a diverse range of data ingestion, processing, and storage technologies.
• Expert-level SQL for complex data engineering and analysis, paired with proficiency in Python and associated data-oriented toolkits.
• A deep understanding of dimensional modeling concepts ((e.g. OLAP cubes, star schemas, kimball architecture vs. alternatives like inmon)
• Proven ability to partner with technical stakeholders to clarify requirements and deliver effective, end-to-end data solutions.
• Proficiency in using AI-assisted tools for code generation, debugging, and optimization, with the ability to rapidly adapt to new schemas and tools in a fast-paced environment.
• Comfortable working "in the trenches" of production systems to test, iterate, and optimize operational workflows.
• Eligible to work in the United States

Bonus Experience

• Experience in enterprise data architecture, service-oriented frameworks, data integration and harmonization, data strategy and governance, high-performing data lakes, data operations and delivery and data ingestion frameworks supporting batch/real-time
• Experience writing and maintaining production ready code in a high level programming language (Python, Java, C++ etc.)
• Experience with data analysis software (Jupyter Notebooks, R, etc.) and data visualization tools (Tableau, Power BI, Superset, etc.). 
• Healthcare experience: either in healthcare data or public health data collection methodologies and workflows
• Experience and comfort working independently with partners for requirements gathering and solution development in an agile software development environment, using JIRA and Asana to manage tasks between technical and client-facing teams

Benefits and Compensation

We aim to make a difference, not just as a company but also as an employer! We are transparent about salaries at all levels of the organization and have a standard, global pay scale for all positions. Our salaries are cost of living adjusted and non-negotiable. The estimated salary range for this position is 82,810 USD - 130,319 USD annually. Your final salary within the range will be dependent on where you are geographically based and might fall outside of this estimated range.

However, the benefits we offer are geared towards having a strong impact on our staff’s well-being. A few of our key benefits are outlined below:

• 100% employer-sponsored medical insurance paired with a generous Health Reimbursement Account (HRA) fund
• Access to voluntary dental and vision insurance plans
• A 401K plan with up to a 4% employer match
• Employee stock option plan
• 30 days paid time off inclusive of holidays
• Unlimited sick time and excellent parental leave policy
• Access to a flex-time policy that allows employees to work based on a flexible work schedule
• Access to an Employee Assistance Program (EAP) through ComPsych

Dimagi is an Equal Opportunity Employer. We celebrate and support diversity and are committed to providing a work environment that is inclusive and free of discrimination and harassment. All employment decisions are based on individual qualifications without regard to race, color, religion, age, sex, sexual orientation, ethnicity, gender identity and expression, national origin, family or parental status, veteran or disability status.

ABOUT PIONEERING INTELLIGENCE 

Pioneering Intelligence builds on Flagship Pioneering’s legacy of founding cutting-edge science and computational ventures, harnessing recent advances in AI, machine learning, and data to accelerate fundamental research and create a portfolio of AI-first companies. As part of Flagship’s integrated model of science, entrepreneurship, and capital, it transforms breakthrough ideas into world-changing companies, elevating the AI advances happening across the ecosystem in human health, sustainability, and beyond.

THE ROLE

We are seeking a Principal Scientist (Embedded ML/Computational) to lead multiple AI/ML or computational projects across early stage ventures, as a part of Flagship’s company origination process. You will define and deliver pragmatic AI strategies, oversee method and platform development (e.g., systems design, drug design, molecular modeling, systems biology, protein design, LLM/agentic workflows), and ensure rigor in model development, benchmarking, scaling, and reporting. You will manage cross functional contributors as applicable, influence company direction, and represent PI to venture teams and external partners. The ideal candidate is a self-directed serial deep diver - someone who can move from protein design one week to mass spec or docking pipelines the next and then spin up LLM based agents that automate scientific workflows. 

KEY RESPONSIBILITIES

• Program Leadership: Lead development, implementation, control, and reporting of several AI/ML or computational projects within assigned ventures in line with broader strategic plans of PI and Flagship, budgets, and timelines. 
• Technical Ownership: Take a specialized technical role on project teams to oversee method development, pipeline development, and LLM based agent/workflow design; drive benchmarking, scaling, and implementation into production grade systems. 
• Best Practices: promote operational excellence in AI projects by educating cross-functional collaborators. 
• Team Leadership: Manage and/or coordinate internal and external scientists/engineers and crossfunctional project teams as applicable; mentor early hires; support recruiting and interview. 
• Planning & Resourcing: Contribute to project planning, including budgets, resources, and timelines; surface risks and tradeoffs early with clear options. 
• Landscape & Strategy: Independently scout emerging literature and the AI/ML landscape; synthesize concepts to propose new development strategies and identify opportunities for PI and venture portfolios. 
• Representation & Community: Represent PI to portfolio companies and external partners; act as a recognized subject matter expert; actively participate in scientific conferences and meetings. 
• Communication & Influence: Influence the course of projects and technical approaches; adapt and present complex findings to diverse audiences to support meaningful interpretation and action. 

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• Master’s, or PhD in a relevant field (e.g., machine learning, mathematics, statistics, computational sciences) with 5+ years' experience scientific/engineering/computational in academic, pharmaceutical, or biotechnology settings; industry AI/ML experience preferred. 
• Experience driving results directly or indirectly through teams of engineers/scientists in dynamic, fastpaced, entrepreneurial, and technical environments. 
• Clear evidence of sustained independent thought and creativity driving high impact, cross disciplinary AI/ML projects. 
• Successful track record of leadership and contribution to decision making on progression of AI/ML models within projects or programs. 
• Depth across multiple core tools and concepts, including Python; modern ML frameworks (PyTorch or JAX/TensorFlow); version control; databases; deep learning architectures; and relevant informatics software. 
• Consistent record of outstanding performance reflected in publications, patents, or high impact internal reports where applicable 

Preferred Qualifications 

• Breadth across domains such as protein modeling/design, proteomics/mass spec, cheminformatics/docking/ADMET, biophysics/MD, and LLM/agentic automation. 
• MLOps expertise: data contracts and lineage (e.g., DVC/LakeFS), experiment tracking (MLflow/W&B), secure AWS infrastructure (S3, Batch/ECS/EKS, SageMaker), Docker, IaC (Terraform/CDK), and CI/CD (GitHub Actions). 
• Generative modeling (diffusion/flow/VAEs) for sequences, graphs, or 3D structures; docking rescoring (e.g., gnina, DiffDock) and pose quality metrics. 
• Workflow orchestration (Airflow/Prefect/Argo), data warehouses (Redshift/Snowflake), vector search (FAISS/pgvector), and lightweight internal tools (FastAPI, Streamlit/Gradio). 
• Experience mentoring early hires, acting as interim Head of ML, and contributing to hiring plans and interview processes at startups. 

WHY PIONEERING INTELLIGENCE

• Operate at the frontier: Build and deploy AI/ML that directly powers discovery and decision making across multiple new ventures. 
• Own the full stack: From scoping and data contracts to models, MLOps, and internal UIs—ship endtoend systems that scientists rely on daily. 
• Compound impact: Convert one off wins into shared libraries and templates adopted across the PI portfolio. 
• Work with founders: Partner closely with venture leadership and PI platform engineers; influence strategy through hands on delivery. 
• Grow fast: Stretch across domains, take on situational leadership, present at conferences, and help shape first ML teams. 

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.

#LI-MB1

The salary range for this role is $208,000 - $286,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Pioneering Intelligence currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Pioneering Intelligence’s good faith estimate as of the date of publication and may be modified in the future.

ABOUT PIONEERING INTELLIGENCE 

Pioneering Intelligence builds on Flagship Pioneering’s legacy of founding cutting-edge science and computational ventures, harnessing recent advances in AI, machine learning, and data to accelerate fundamental research and create a portfolio of AI-first companies. As part of Flagship’s integrated model of science, entrepreneurship, and capital, it transforms breakthrough ideas into world-changing companies, elevating the AI advances happening across the ecosystem in human health, sustainability, and beyond.

THE ROLE

We are seeking a Principal Scientist (Embedded ML/Computational) to lead multiple AI/ML or computational projects across early stage ventures, as a part of Flagship’s company origination process. You will define and deliver pragmatic AI strategies, oversee method and platform development (e.g., systems design, drug design, molecular modeling, systems biology, protein design, LLM/agentic workflows), and ensure rigor in model development, benchmarking, scaling, and reporting. You will manage cross functional contributors as applicable, influence company direction, and represent PI to venture teams and external partners. The ideal candidate is a self-directed serial deep diver - someone who can move from protein design one week to mass spec or docking pipelines the next and then spin up LLM based agents that automate scientific workflows. 

KEY RESPONSIBILITIES

• Program Leadership: Lead development, implementation, control, and reporting of several AI/ML or computational projects within assigned ventures in line with broader strategic plans of PI and Flagship, budgets, and timelines. 
• Technical Ownership: Take a specialized technical role on project teams to oversee method development, pipeline development, and LLM based agent/workflow design; drive benchmarking, scaling, and implementation into production grade systems. 
• Best Practices: promote operational excellence in AI projects by educating cross-functional collaborators. 
• Team Leadership: Manage and/or coordinate internal and external scientists/engineers and crossfunctional project teams as applicable; mentor early hires; support recruiting and interview. 
• Planning & Resourcing: Contribute to project planning, including budgets, resources, and timelines; surface risks and tradeoffs early with clear options. 
• Landscape & Strategy: Independently scout emerging literature and the AI/ML landscape; synthesize concepts to propose new development strategies and identify opportunities for PI and venture portfolios. 
• Representation & Community: Represent PI to portfolio companies and external partners; act as a recognized subject matter expert; actively participate in scientific conferences and meetings. 
• Communication & Influence: Influence the course of projects and technical approaches; adapt and present complex findings to diverse audiences to support meaningful interpretation and action. 

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• Master’s, or PhD in a relevant field (e.g., machine learning, mathematics, statistics, computational sciences) with 5+ years' experience scientific/engineering/computational in academic, pharmaceutical, or biotechnology settings; industry AI/ML experience preferred. 
• Experience driving results directly or indirectly through teams of engineers/scientists in dynamic, fastpaced, entrepreneurial, and technical environments. 
• Clear evidence of sustained independent thought and creativity driving high impact, cross disciplinary AI/ML projects. 
• Successful track record of leadership and contribution to decision making on progression of AI/ML models within projects or programs. 
• Depth across multiple core tools and concepts, including Python; modern ML frameworks (PyTorch or JAX/TensorFlow); version control; databases; deep learning architectures; and relevant informatics software. 
• Consistent record of outstanding performance reflected in publications, patents, or high impact internal reports where applicable 

Preferred Qualifications 

• Breadth across domains such as protein modeling/design, proteomics/mass spec, cheminformatics/docking/ADMET, biophysics/MD, and LLM/agentic automation. 
• MLOps expertise: data contracts and lineage (e.g., DVC/LakeFS), experiment tracking (MLflow/W&B), secure AWS infrastructure (S3, Batch/ECS/EKS, SageMaker), Docker, IaC (Terraform/CDK), and CI/CD (GitHub Actions). 
• Generative modeling (diffusion/flow/VAEs) for sequences, graphs, or 3D structures; docking rescoring (e.g., gnina, DiffDock) and pose quality metrics. 
• Workflow orchestration (Airflow/Prefect/Argo), data warehouses (Redshift/Snowflake), vector search (FAISS/pgvector), and lightweight internal tools (FastAPI, Streamlit/Gradio). 
• Experience mentoring early hires, acting as interim Head of ML, and contributing to hiring plans and interview processes at startups. 

WHY PIONEERING INTELLIGENCE

• Operate at the frontier: Build and deploy AI/ML that directly powers discovery and decision making across multiple new ventures. 
• Own the full stack: From scoping and data contracts to models, MLOps, and internal UIs—ship endtoend systems that scientists rely on daily. 
• Compound impact: Convert one off wins into shared libraries and templates adopted across the PI portfolio. 
• Work with founders: Partner closely with venture leadership and PI platform engineers; influence strategy through hands on delivery. 
• Grow fast: Stretch across domains, take on situational leadership, present at conferences, and help shape first ML teams. 

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.

#LI-MB1

The salary range for this role is $208,000 - $286,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Pioneering Intelligence currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Pioneering Intelligence’s good faith estimate as of the date of publication and may be modified in the future.

ABOUT PIONEERING INTELLIGENCE 

Pioneering Intelligence builds on Flagship Pioneering’s legacy of founding cutting-edge science and computational ventures, harnessing recent advances in AI, machine learning, and data to accelerate fundamental research and create a portfolio of AI-first companies. As part of Flagship’s integrated model of science, entrepreneurship, and capital, it transforms breakthrough ideas into world-changing companies, elevating the AI advances happening across the ecosystem in human health, sustainability, and beyond.

THE ROLE

We are seeking a Principal Scientist (Embedded ML/Computational) to lead multiple AI/ML or computational projects across early stage ventures, as a part of Flagship’s company origination process. You will define and deliver pragmatic AI strategies, oversee method and platform development (e.g., systems design, drug design, molecular modeling, systems biology, protein design, LLM/agentic workflows), and ensure rigor in model development, benchmarking, scaling, and reporting. You will manage cross functional contributors as applicable, influence company direction, and represent PI to venture teams and external partners. The ideal candidate is a self-directed serial deep diver - someone who can move from protein design one week to mass spec or docking pipelines the next and then spin up LLM based agents that automate scientific workflows. 

KEY RESPONSIBILITIES

• Program Leadership: Lead development, implementation, control, and reporting of several AI/ML or computational projects within assigned ventures in line with broader strategic plans of PI and Flagship, budgets, and timelines. 
• Technical Ownership: Take a specialized technical role on project teams to oversee method development, pipeline development, and LLM based agent/workflow design; drive benchmarking, scaling, and implementation into production grade systems. 
• Best Practices: promote operational excellence in AI projects by educating cross-functional collaborators. 
• Team Leadership: Manage and/or coordinate internal and external scientists/engineers and crossfunctional project teams as applicable; mentor early hires; support recruiting and interview. 
• Planning & Resourcing: Contribute to project planning, including budgets, resources, and timelines; surface risks and tradeoffs early with clear options. 
• Landscape & Strategy: Independently scout emerging literature and the AI/ML landscape; synthesize concepts to propose new development strategies and identify opportunities for PI and venture portfolios. 
• Representation & Community: Represent PI to portfolio companies and external partners; act as a recognized subject matter expert; actively participate in scientific conferences and meetings. 
• Communication & Influence: Influence the course of projects and technical approaches; adapt and present complex findings to diverse audiences to support meaningful interpretation and action. 

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• Master’s, or PhD in a relevant field (e.g., machine learning, mathematics, statistics, computational sciences) with 5+ years' experience scientific/engineering/computational in academic, pharmaceutical, or biotechnology settings; industry AI/ML experience preferred. 
• Experience driving results directly or indirectly through teams of engineers/scientists in dynamic, fastpaced, entrepreneurial, and technical environments. 
• Clear evidence of sustained independent thought and creativity driving high impact, cross disciplinary AI/ML projects. 
• Successful track record of leadership and contribution to decision making on progression of AI/ML models within projects or programs. 
• Depth across multiple core tools and concepts, including Python; modern ML frameworks (PyTorch or JAX/TensorFlow); version control; databases; deep learning architectures; and relevant informatics software. 
• Consistent record of outstanding performance reflected in publications, patents, or high impact internal reports where applicable 

Preferred Qualifications 

• Breadth across domains such as protein modeling/design, proteomics/mass spec, cheminformatics/docking/ADMET, biophysics/MD, and LLM/agentic automation. 
• MLOps expertise: data contracts and lineage (e.g., DVC/LakeFS), experiment tracking (MLflow/W&B), secure AWS infrastructure (S3, Batch/ECS/EKS, SageMaker), Docker, IaC (Terraform/CDK), and CI/CD (GitHub Actions). 
• Generative modeling (diffusion/flow/VAEs) for sequences, graphs, or 3D structures; docking rescoring (e.g., gnina, DiffDock) and pose quality metrics. 
• Workflow orchestration (Airflow/Prefect/Argo), data warehouses (Redshift/Snowflake), vector search (FAISS/pgvector), and lightweight internal tools (FastAPI, Streamlit/Gradio). 
• Experience mentoring early hires, acting as interim Head of ML, and contributing to hiring plans and interview processes at startups. 

WHY PIONEERING INTELLIGENCE

• Operate at the frontier: Build and deploy AI/ML that directly powers discovery and decision making across multiple new ventures. 
• Own the full stack: From scoping and data contracts to models, MLOps, and internal UIs—ship endtoend systems that scientists rely on daily. 
• Compound impact: Convert one off wins into shared libraries and templates adopted across the PI portfolio. 
• Work with founders: Partner closely with venture leadership and PI platform engineers; influence strategy through hands on delivery. 
• Grow fast: Stretch across domains, take on situational leadership, present at conferences, and help shape first ML teams. 

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.

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The salary range for this role is $208,000 - $286,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Pioneering Intelligence currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Pioneering Intelligence’s good faith estimate as of the date of publication and may be modified in the future.

About the team

Roku is the No. 1 TV streaming platform in the U.S., Canada, and Mexico with 70+ millions of active accounts. Roku pioneered streaming to the TV and continues to innovate and lead the industry. We believe Roku’s continued success relies on its investment in our machine learning/ML recommendation engine. Roku enables our users to access millions of contents including movies, episodes, news, sports, music and channels from all around the world. 

About the role 

The depth of query, content and user understanding using ML is key to user happiness in their search journey. Solving this customer problem is why we're actively looking for a Senior Machine Learning Engineer, Search & Recommendations to drive further innovation in search and discovery. The person in this role will leverage their technical skills, business intuition, and analytical thinking to build best of class AI powered products. Hence, communication and presentation skills are important. The role requires both high technical acumen and problem-solving abilities, motivation, and exceptional attention to detail. Every day, you'll look at what exists and find ways to make it better.

What you'll be doing

• Apply state of the art ML on search using techniques in deep learning, bandits, transformers, LLMs, causal inference, and optimisations to make our users more delighted and engaged on the platform
• Run online AB tests and analyse them against the critical business KPIs
• Collaborate with US engineering teams as well as cross-functional teams to translate business requirements into technical specifications
• Nurture our ML ecosystem to make it withstand scale, developer velocity and future business shifts
• Provide technical leadership to drive technical and ML roadmap for search ranking and monetisation
• Help in recruiting new engineers. Interview, train, and mentor new team members

We're excited if you have

• 8+ years of experience (or PhD with 6 years of experience) applying Machine Learning to concrete problems at large-scale in domains like recommendation or search or ads
• Strong CS fundamentals. Should be able covert ideas to code with ease
• Good understanding of machine learning fundamentals like classification, deep neural nets, and sequence-based models. Familiarity with modern NLP stack and multi-modal representation learning is a plus
• We'd love to see that you've worked with big data systems (Spark, S3, and Airflow) and can program (Java, Scala, or Python) 
• Good understanding of system architecture. Have experience in big data technologies and streaming architecture, data pipelines, etc.
• MS in Computer Science, Statistics, or related field, but a Ph.D. in CS or related fields is preferred

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About The Team

The Roku Enterprise Engineering team is at the forefront of building a robust, integrated, and scalable platform that powers critical business processes across the organization. As a cornerstone of Roku's corporate strategy, this team is instrumental in automating workflows across all Business Systems, including Supply Chain, Finance, Sales Operations, and Human Resources. By challenging traditional approaches to workflow automation, the team leverages cutting-edge Engineering practices and API-driven design to streamline internal processes, boost efficiency, and deliver innovative solutions.

The team's expertise spans a wide range of technologies, including Java and Python-based MicroServices, AWS/GCP cloud backend systems, Big Data technologies like Hive and Spark, and modern Web applications. With a globally distributed presence across the US, India and Europe, the team thrives on collaboration, bringing together diverse perspectives to solve complex challenges. At the heart of their success is a shared commitment to technical excellence, creativity, a strong sense of ownership, and a collaborative spirit that drives impactful results for Roku's business operations.

About The Role

As a senior technical lead, you consider yourself a platform services developer and developing innovative solutions using modern software frameworks and paradigms. You are self-driven and problem solver, with a strong background in building large-scale software platform and applications. You are execution focused and would develop a reputation for repeatedly delivering projects on-time.

What you'll be doing

• Design, develop and deploy scalable web applications and services, being part of everything from contributing to web technology and framework stack, to use case and data model design
• Drive architecture discussions, take ownership and responsibility over new projects, and deliver high quality software with tight timeline
• Partner with security and compliance teams to ensure the application meets compliance, security and audit requirements
• Participate in the continual improvement of engineering tools, cloud-based technologies/services, and process
• Define and participate in Agile development process, including scoping, technical design, estimation effort, coding, testing, debugging, code reviews, maintenance and support
• Collaborate with cross-function teams and demonstrate great communication skills

We're excited if you have

• 5+ years of experience in delivery multi-tier, highly scalable, distributed web application
• Deep understanding in software architecture, object-oriented design principles, and data structures
• Extensive experience in developing microservices using Java, Python
• Good experience in Test driven development and automating test cases using Java/ Python
• Experience in SQL / NoSQL (Oracle, Cassandra) database design
• Demonstrated ability to be proactive, self-driven, and make practical trade-offs based on business needs, entrepreneurial spirit
• Excellent verbal and written communication skills
• BS or MS degree in Computer Science or equivalent
• Experience in distributed computing frameworks like - Hive/Hadoop, Apache Spark
• Experience in developing Finance or HR related applications
• Experience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, Lambda
• Working experience with Terraform
• Experience in creating workflows for Apache Airflow

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About The Team

The Roku Enterprise Engineering team is at the forefront of building a robust, integrated, and scalable platform that powers critical business processes across the organization. As a cornerstone of Roku's corporate strategy, this team is instrumental in automating workflows across all Business Systems, including Supply Chain, Finance, Sales Operations, and Human Resources. By challenging traditional approaches to workflow automation, the team leverages cutting-edge Engineering practices and API-driven design to streamline internal processes, boost efficiency, and deliver innovative solutions.

The team's expertise spans a wide range of technologies, including Java and Python-based MicroServices, AWS/GCP cloud backend systems, Big Data technologies like Hive and Spark, and modern Web applications. With a globally distributed presence across the US, India and Europe, the team thrives on collaboration, bringing together diverse perspectives to solve complex challenges. At the heart of their success is a shared commitment to technical excellence, creativity, a strong sense of ownership, and a collaborative spirit that drives impactful results for Roku's business operations.

About The Role

As a senior technical lead, you consider yourself a platform services developer and developing innovative solutions using modern software frameworks and paradigms. You are self-driven and problem solver, with a strong background in building large-scale software platform and applications. You are execution focused and would develop a reputation for repeatedly delivering projects on-time.

What you'll be doing

• Design, develop and deploy scalable web applications and services, being part of everything from contributing to web technology and framework stack, to use case and data model design
• Drive architecture discussions, take ownership and responsibility over new projects, and deliver high quality software with tight timeline
• Partner with security and compliance teams to ensure the application meets compliance, security and audit requirements
• Participate in the continual improvement of engineering tools, cloud-based technologies/services, and process
• Define and participate in Agile development process, including scoping, technical design, estimation effort, coding, testing, debugging, code reviews, maintenance and support
• Collaborate with cross-function teams and demonstrate great communication skills

We're excited if you have

• 5+ years of experience in delivery multi-tier, highly scalable, distributed web application
• Deep understanding in software architecture, object-oriented design principles, and data structures
• Extensive experience in developing microservices using Java, Python
• Good experience in Test driven development and automating test cases using Java/ Python
• Experience in SQL / NoSQL (Oracle, Cassandra) database design
• Demonstrated ability to be proactive, self-driven, and make practical trade-offs based on business needs, entrepreneurial spirit
• Excellent verbal and written communication skills
• BS or MS degree in Computer Science or equivalent
• Experience in distributed computing frameworks like - Hive/Hadoop, Apache Spark
• Experience in developing Finance or HR related applications
• Experience with following cloud services: AWS Elastic Beanstalk, EC2, S3, CloudFront, RDS, DynamoDB, VPC, Elastic Cache, Lambda
• Working experience with Terraform
• Experience in creating workflows for Apache Airflow

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Philo: a streaming service for TV and movie lovers

At Philo, we’re a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented — in short, we’re building the TV experience that we’ve always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences.

Data at Philo

Data underpins everything we do at Philo: making informed business decisions; analyzing and improving the quality of our streaming experience; running product experiments to optimize our signup flows and improve user journeys; and making it effortless for our users to find the perfect thing to watch. Philo serves over a billion streams to its users every year, generating a wealth of data that we leverage at all levels of the organization. Philo’s data platform operates at very large scale, processing trillions of events annually in a petabyte-scale data lake and supporting thousands of data workflows and analytical queries that power decision-making across the company.

Philo’s Data Engineering team encompasses both data engineering and analytics engineering, and we’re looking for people who are comfortable working on complex data infrastructure and modeling challenges that support critical business functions across our streaming services. You’ll be working closely with other data scientists, analysts, and engineers to build and deploy solutions directly for our service – this work spans both foundational data platform work like data warehouse architecture, metric governance, and semantic consistency across our entire data stack. In addition, you’ll work with departments across the organization to understand their data needs and deliver high-performance, reliable data systems to help the entire team thrive.

We are passionate about building robust, scalable data infrastructure and providing a high-quality data platform for the entire company, using both cutting-edge technologies and proven engineering practices in close collaboration with every department. To complete our work, we build on modern tools including AWS-native services, dbt, Segment, Snowflake, AWS SageMaker, Spark, Avo, BigEye and more.

Some of the recent projects that data and analytics engineers at Philo have worked on include building new models for key financial data, dbt model design, data warehouse cluster upgrades and maintenance, per-query infra cost optimization, implementation of Apache Iceberg data storage, benchmarking & improving data warehouse performance, and evaluating alternative data warehouse technologies.

The Role

We're seeking a senior technical and foundational leader to own and drive the vision, strategy, and execution of our Data Engineering team, encompassing both the data engineering and analytics engineering  functions at Philo. This is a strategic and high-impact role: you'll set the long-term direction for our entire data platform, lead and grow a team of data and analytics engineers, and roll up your sleeves to architect and build alongside them. The ideal candidate has owned both disciplines before — data infrastructure and analytics engineering — and brings strong opinions on how to structure a high-velocity, high-trust data organization. 

Responsibilities:

• Own the vision and technical strategy for data engineering and analytics engineering at Philo, setting the direction for how data is ingested, modeled, and delivered across the organization
• Own the team’s roadmap, balancing strategic long-term investments with near-term stakeholder needs
• Lead and grow the Data Engineering team, including hiring, career development, performance management, and supporting the team in generally thriving
• Lead the design and implementation of Philo's data platform architecture, including  setting technical standards and best practices for data engineering and analytics engineering work
• Collaborate with cross-functional teams to understand data platform needs and translate business requirements into technical solutions
• Build and maintain stakeholder trust in data and reporting — ensuring that business teams have reliable, well-documented, and well-understood data products
• Design scalable data pipelines and infrastructure; drive technical decisions with a focus on long-term sustainability
• Implement data governance, security, and quality control processes as needed
• Ultimately, deliver on the alchemy of transforming raw, messy application data into trusted business insight through scalable dimensional modeling and a metric layer that faithfully reflects product and customer behavior.

Key Qualifications:

• 10+ years of professional experience spanning data engineering and analytics engineering, ideally with a few years working on high-volume data platforms
• 4+ years of experience managing and leading data teams, with demonstrated experience owning both data engineering and analytics engineering functions at a prior organization
• Deep expertise in modern data stack technologies, particularly AWS data services, Snowflake, dbt, Airflow, Airbyte, Python, and SQL
• Deep expertise in analytics engineering, including dbt model design, dimensional modeling, and delivering trusted, business-facing data products
• Strong people management skills with experience providing coaching, performance feedback, and career development guidance to direct reports.
• Track record of improving stakeholder trust in reporting and data quality across an organization
• Strong track record of designing and implementing data platforms
• Excellent communication skills with technical and non-technical stakeholders, simplifying complex data concepts for various business audiences

Ideal Qualifications:

• Experience in media/streaming industry with understanding of video delivery analytics and metrics
• Demonstrated experience driving organizational alignment around data definitions, metrics, and a single source of truth
• Experience with data governance and compliance requirements
• Background in implementing data quality frameworks

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 streaming live and on-demand, 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.

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.

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

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: $240K - $275K
• Boston, DC Metro, Los Angeles, Seattle: $225K - $260K
• Denver, Atlanta, Austin, Las Vegas, Sacramento, Chicago: $215K - $250K
• Texas, Florida: $200K - $235K

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.