About the team

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

About the role

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

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

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

What you'll be doing

• Support and maintain existing automation tools and technology
• Develop and release new E2E automation support and tools
• Debug issues to improve the quality of automated test tools and frameworks
• Conduct code reviews to improve code quality and optimization
• Promote coding conventions and standards for code re-usability and cleanliness
• Document Feature guides, identify and formulate user requirements, product behavior
• Mentor less experienced engineers and driving automation development
• Assist in monitoring and maintenance of critical systems

We're excited if you have

• 5+ years of hands-on experience with automation systems
• 5+ years of programming experience, preferably with Python
• Bachelor’s degree in Computer Science or related
• Proficient in linux, Python based test automation frameworks and tools using REST APIs
• Hands on experience in development/integration of E2E test automation framework and tools for embedded software devices
• Experienced in developing and maintaining web based tools using Javascript, React
• Proficiency with DevOps, continuous integration tools (Jenkins, Gitlab CI, Teamcity, Docker and Kubernetes)
• Experience with CI/CD pipeline development and deployment via AWS or GCP cloud technologies
• Experience with Unit Testing frameworks – pytest/pyunit and cypress, playwright for UI testing
• Experience of developing web applications using Flask, FastAPI, Django, Nginx
• Experience and knowledge of using generative AI
• Expert problem-solving and technical troubleshooting skills
• Ability to learn new technologies quickly
• A self-directed professional able to work independently
• Ability to work through ambiguous requirements and being flexible/adaptable to change
• Comfortable and experienced working with cross-functional peers and internal stakeholders across European and US timezones
• Excellent communication and collaborative skills
• Experience with retail Consumer Electronic (CE) devices, ideally in the Over The Top (OTT) streaming domain
• Previous experience with Non-Functional Testing (Performance Testing, Stress Testing)
• Knowledge of network technologies and libraries such as TCP/IP and HTTP
• Previous experience and knowledge of image processing and inferencing, creating computer vision capabilities for visual testing

#LI-AB3

About the team

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

About the role

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

What you'll be doing

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

We're excited if you have

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

#LI-NM1

About the Team

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

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

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

About the Role

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

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

What You’ll Be Doing

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

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

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

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

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

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

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

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

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

We’re Excited If You Have

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

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

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

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

• Proven ability to evaluate models and communicate insights effectively

• Experience building APIs with frameworks such as GraphQL or REST

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

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

#LI-PA1

About the team

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

About the role

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

What you'll be doing

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

We're excited if you have

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

#LI-NM1

About the team

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

About the role

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

What you'll be doing

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

We're excited if you have

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

#LI-NM1

About us 

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

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

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

Job Summary

As a Graduate Machine Learning Engineer in the Applied AI team at Graphcore, you will contribute to advancing AI technology by developing and optimising AI models tailored to our specialised hardware. Working closely with the Software development and Research teams, you will play a critical role in identifying opportunities to innovate and differentiate Graphcore’s technology. This role is ideal for someone who loves working hands-on with models, has a strong foundation in ML fundamentals, and wants to push the boundaries of AI performance in real-world systems. 

The Team

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

Responsibilities and Duties

• Implement state-of-the-art machine learning models and optimise them for performance and accuracy, scaling to 1000s of accelerators. 
• Evaluate new software releases, provide feedback to software engineering teams, make necessary code fixes, and conduct code reviews. 
• Benchmark models and key model components to identify performance bottlenecks and improve model efficiency. 
• Design and conduct experiments on novel AI methods, analyse and report results clearly. 
• Collaborate with Research, Software, and Product teams to define, build, and test Graphcore’s next generation of AI hardware. 
• Stay current with AI research and actively engage with the broader AI and open-source community. 

Candidate Profile 

Essential:

• Bachelor’s/Master's degree in Machine Learning, Computer Science, Maths, Data Science, or related field. 
• Proficiency in deep learning frameworks such as PyTorch/JAX and strong software development skills. 
• Solid understanding of deep learning fundamentals — architectures, optimisation, evaluation, and scaling. 
• Capable of designing, executing and reporting from ML experiments. 
• Comfortable working in a fast-moving, occasionally ambiguous environment. 
• Enjoy cross-functional work collaborating with other teams. 

Desirable:

Experience in one or more of: 

• Development of deep learning models including large generative models for language, vision and other modalities; 
• Low-precision/efficient compute; 
• Distributed training of large-scale ML models. 
• Experience writing high performance C++/Triton/CUDA kernels. 
• Contributions to open-source projects or published research. 
• Familiarity with cloud platforms and ML infrastructure. 
• Enthusiasm for presenting, publishing, or engaging in the AI community. 

Benefits

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

About the Role:

Stylus Medicine is seeking an intellectually curious and creative Director, who will serve as a key scientific leader on our Platform team, owning the computational strategy that drives large serine recombinase (LSR) engineering and clinical translation. This role sits at the intersection of protein engineering, multi-omics analysis, and AI/ML-driven design and will lead a high-impact team spanning NGS and computational biology while driving the analytical infrastructure and predictive capabilities needed to advance our proprietary LSR platform from discovery through translation.

Key Responsibilities & Accountabilities:

• Lead and develop a team of NGS and computational biology scientists, setting technical direction, mentoring team members, and fostering a collaborative, high-performance culture
• Lead computational efforts to design and optimize LSRs and related genome engineering proteins for genetic medicine applications, integrating sequence-function, structure-function, and protein-DNA interaction datasets to guide engineering campaigns
• Lead analysis of NGS data from LSR experiments — including amplicon sequencing, WGS, hybrid capture, and long-read sequencing — to quantify on-target efficiency and genome-wide specificity
• Build, apply, and critically evaluate predictive and generative models for protein variant and library design — including rigorous benchmarking of AI/ML approaches such as protein language models, structure prediction tools, and generative design frameworks
• Integrate proprietary screening data with public evolutionary and structural datasets to prioritize variants and identify engineering levers for activity, specificity, and developability
• Oversee the design, implementation, and deployment of robust, scalable computational pipelines for multi-omics data analysis, ensuring accuracy, reproducibility, and maintainability
• Provide scientific input into platform strategy, translating computational insights into actionable directions for the broader team
• Partner closely with the Screening, Genome Engineering, and NGS teams to design experiments, interpret complex datasets, and refine engineering hypotheses
• Contribute to patent filings, regulatory submissions, and publications

Qualifications & Skills:

• PhD in Computational Biology, Bioinformatics, Protein Engineering, Machine Learning or a related quantitative discipline, with 10+ years or Master’s with 14+ years of industry experience
• Demonstrated research in protein modeling, protein design, or computational biology through publications, preprints, or equivalent industry contributions
• Hands-on experience applying AI/ML methods to protein variant and library design, including protein language models, structure prediction, and generative design approaches (e.g., AlphaFold2/3, RFdiffusion, ProteinMPNN, ESM)
• Expert-level proficiency in Python and/or R, with deep familiarity with data science libraries (e.g., Pandas, NumPy, Bioconductor, SciPy, PyTorch, or JAX)
• Experience with cloud computing platforms and workflow management systems
• Excellent communication and documentation skills, with a track record of effective collaboration in fast-paced, interdisciplinary environments

Pay Range; $245,000 - $265,000

Your Impact at LILA

As a Robotics Scientist at Lila, you will lead the research and development of autonomous robotic systems that serve as the intelligent physical infrastructure of our scientific superintelligence platform. You’ll develop novel algorithms and deploy intelligent robotic solutions that interact seamlessly with human scientists and complex lab environments. Your work will accelerate our mission by enabling fully autonomous workflows for scientific discovery, combining cutting-edge robotics, machine learning, and systems engineering.

What You'll Be Building

• Pioneering approaches for precise and dexterous robotic manipulation that leverage foundation models, reinforcement learning, diffusion-based methods, and human guidance to enable adaptive and intelligent robotic systems capable of complex tasks across diverse scientific environments
• Developing novel human-robot interaction frameworks that incorporate imitation learning, and learning from human guidance, feedback, demonstrations and corrections, creating intelligent robotic agents that can seamlessly integrate with human scientific workflows and rapidly adapt to new experimental contexts
• Advancing dexterous manipulation research through cutting-edge machine learning approaches, including diffusion models and adaptive learning algorithms, that synthesize multi-modal sensing (tactile, visual, and language) to develop generative skill representation sand sophisticated motor learning policies for intelligent robotic systems
• Designing autonomous robotic systems with trust calibration mechanisms, enabling intelligent agents that can dynamically adjust their behaviors based on contextual information in complex scientific tasks

What You’ll Need to Succeed

• Ph.D. in Robotics, Machine Learning, Computer Science, or a related field with demonstrated expertise in foundation models for robotic learning
• Advanced proficiency in reinforcement learning, diffusion-based methods, imitation learning, and adaptive learning algorithms for robotic manipulation
• Expert-level experience with machine learning frameworks (PyTorch, TensorFlow) and deep learning architectures for developing foundation models, with specific expertise in diffusion-based generative models for robotics
• Proven track record of developing multi-modal perception systems integrating tactile, visual, language and other contextual sensing for intelligent robotic agents
• Strong publication record in robot learning, demonstrating innovative approaches to trust calibration, contextual learning, and generative robotic skill learning

Bonus Points For

• Research contributions to foundation models and diffusion methods in robotics
• Experience with large-scale machine learning model development, particularly generative and diffusion-based approaches
• Expertise in human-in-the-loop learning, correction-based training paradigms, and diffusion-guided skill transfer
• Demonstrated ability to translate theoretical machine learning research, especially diffusion and generative models, into practical robotic implementations

About the team

At Roku, the UI Systems team builds the high-performance engines and core graphics infrastructure that power millions of devices. We own the low-level C++ frameworks, rendering pipelines, and system architectures that enable smooth navigation and rich animations. Our work sits at the intersection of hardware and software, where we optimize graphics rendering, memory management, and layout engines to ensure a consistent, lightning-fast experience across our entire device portfolio. We operate in a collaborative, high-trust environment, partnering closely with firmware and silicon teams to push the boundaries of what’s possible on embedded hardware.

About the role

As a Senior Software Engineer, you will be a key architect of the core systems that underpin Roku’s user experience. You will design and implement performance-critical code within our UI engine, focusing on graphics primitives, memory efficiency, and hardware acceleration. You’ll tackle complex systems-level challenges—such as optimizing frame rates on resource-constrained hardware and building robust APIs for higher-level frameworks. This role is ideal for engineers who thrive on low-level systems programming, care about performance down to the microsecond, and want to build the high-performance foundations that power the future of television.

What you’ll be doing

• Architect and optimize core C++ UI frameworks and rendering engines to ensure buttery-smooth performance across a diverse range of hardware profiles.
• Lead technical investigations into system-level bottlenecks, memory leaks, and GPU/CPU synchronization issues.
• Develop and maintain low-level graphics APIs and layout systems that serve as the backbone for Roku’s application ecosystem.
• Integrate AI/ML capabilities at the systems level, leveraging generative AI tools to optimize code generation and automate performance profiling.
• Collaborate with firmware and driver teams to leverage hardware-specific optimizations and ensure seamless integration with the underlying OS.
• Mentor junior developers through deep-dive code reviews, architectural design sessions, and technical documentation of core systems.
• Drive engineering excellence by implementing advanced debugging tools, automated performance regression suites, and modern C++ best practices.

We’re excited if you have

• Minimum of 5+ years of software engineering experience with a heavy focus on C++ (C++14/17/20).
• Deep understanding of systems programming, including memory management, multi-threading, and hardware-software abstraction layers.
• Experience with graphics APIs (e.g., OpenGL, Vulkan, or proprietary embedded graphics stacks) and rendering pipelines.
• Proficiency in Python for tooling and automation, with a working knowledge of BrightScript or JavaScript being a significant plus.
• Strong root cause analysis skills, specifically using tools like GDB, Valgrind, or platform-specific profilers.
• Knowledge of AI applications and hands-on experience using generative AI tools to accelerate systems-level development.
• A proactive mindset with a passion for squeezing every drop of performance out of embedded systems and a commitment to data-driven optimization.

About the team

At Roku, the UI team builds the foundational frameworks, tooling, and high‑performance UI components that power experiences across millions of devices. We own the middleware and UI layers that enable smooth navigation, responsive interactions, rich animations, and consistent developer workflows across the platform. Our work spans graphics rendering, layout and animation systems, performance optimization, and developer APIs that make it easy to create reliable, visually compelling applications at scale. We operate in a collaborative, high‑trust environment and partner closely with firmware, platform, and product teams to ensure the end‑to‑end experience is fast, robust, and ready for what’s next.

About the role

As a Senior Software Engineer on the UI team, you’ll design, implement, and optimize systems that underpin Roku’s user experience and developer platform. You’ll work on performance‑critical code paths for graphics rendering, animation, layout, and UI frameworks, ensuring buttery‑smooth visuals and instant responsiveness across a wide range of devices. You’ll help shape core architecture, collaborate across the stack with hardware, firmware, and application teams, and see your work directly impact tens of millions of users. This role is ideal for engineers who love deep technical problem‑solving, care about performance down to the last millisecond, and want to build the invisible foundations that make great user experiences possible.

What you’ll be doing

• Build scalable UI features optimized for millions of users
• Lead technical investigations and architect solutions across middleware, UI frameworks, and rendering pipelines
• Integrate AI/ML capabilities and leverage generative AI tools to accelerate development and improve developer productivity
• Collaborate with cross‑functional teams to deliver global platform features with measurable performance and reliability gains
• Develop engineering tooling, frameworks, and automated workflows that raise developer efficiency and code quality
• Mentor junior developers through design reviews, pair programming, and clear technical documentation
• Stay current with platform, graphics, and AI trends; proactively identify opportunities to improve performance and developer experience

We’re excited if you have

• Minimum of 5+ years of software engineering experience with a focus on UI frameworks or application development
• Advanced BrightScript (or JavaScript‑like) skills and proficiency in Python
• Experience using Typescript is a plus!
• Knowledge and hands-on experience using C++
• Strong root cause analysis skills and clear, effective technical communication
• Knowledge of AI applications and hands‑on experience with generative AI tools and workflows
• A proactive mindset with passion for continuous learning, fast iteration, and data‑driven optimization

#LI-NM1

Your Impact at LILA

As a Principal Security Engineer focused on AI Security, you will define and drive the technical strategy for securing how AI is used across Lila's enterprise. You will operate as a senior individual contributor, partnering with IT and business teams to ensure safe and compliant adoption of AI tools and platforms.

While Lila builds AI-powered systems, this role is primarily focused on securing the use of third-party and internally deployed AI tools across the enterprise — ensuring sensitive data, intellectual property, and scientific workflows are protected as AI becomes deeply embedded in how work gets done.

What You'll Be Building

• Enterprise AI Security Strategy — Define and implement security controls and guardrails for the use of AI tools (e.g., LLM APIs, SaaS AI platforms, and internal AI services) across the organization.
• AI Gateway & Agentic Gateway Security — Design and implement AI gateway controls to manage and monitor access to external and internal AI systems. Secure agentic workflows by enforcing identity, authorization, tool-use constraints, and policy controls for autonomous or semi-autonomous agents.
• AI Red Teaming & Adversarial Testing — Conduct red teaming and adversarial testing focused on enterprise AI usage, including prompt injection, data exfiltration, jailbreaks, and abuse of connected tools and plugins.
• Data Protection for AI Usage — Develop and enforce controls to prevent sensitive data leakage through AI systems, including input/output filtering, data classification, tokenization, and secure handling of prompts, embeddings, and outputs.
• Multi-Layer AI Security (Network, Endpoint, Data) — Integrate AI security into existing enterprise security layers: network visibility and control over AI service access, API traffic inspection, and zero trust enforcement; endpoint security for developer machines, research environments, browsers, and plugins; data layer controls ensuring proper handling of sensitive data when interacting with AI systems.
• AI Threat Modeling (Enterprise Context) — Develop threat models focused on enterprise AI usage, including risks such as data leakage, prompt injection, model misuse, supply chain risks from AI vendors, and unauthorized agent actions.
• Vendor & Platform Security — Assess and guide secure adoption of third-party AI vendors and platforms, including evaluating data handling practices, model behavior, and integration risks.
• Incident Response for AI Usage — Define and support response approaches for AI-related incidents, such as sensitive data exposure, policy violations, or misuse of AI tools.
• Cross-Functional Technical Leadership — Partner with Legal, Compliance, IT, and Engineering to align AI usage with regulatory requirements, data governance policies, and responsible AI practices.
• Security Enablement — Contribute to internal guidance and education on safe AI usage, including secure prompting, data handling, and appropriate use of AI tools.
• Security Tooling & Implementation — Evaluate and implement tooling for AI security, including AI gateways, DLP integrations, monitoring solutions, and policy enforcement mechanisms.

What You’ll Need to Succeed

• 8+ years of experience in information security, with strong expertise in enterprise, cloud, or application security.
• Hands-on experience designing and implementing security controls in enterprise environments.
• Familiarity with AI/ML systems and how modern AI tools (LLMs, copilots, APIs) are used in practice.
• Experience with cloud platforms (AWS/GCP), SaaS security, and zero trust architectures.
• Experience with data protection technologies (e.g., DLP, data classification, access controls).
• Practical experience with threat modeling, red teaming, or adversarial testing.
• Strong communication and influence skills across technical and non-technical stakeholders.

Bonus Points For

• Experience securing enterprise use of LLMs, copilots, or generative AI platforms.
• Familiarity with AI gateways, prompt filtering, or model interaction controls.
• Experience evaluating or securing third-party AI vendors and APIs.
• Background in regulated environments (biotech, healthcare, defense, or government).
• Experience with browser security, endpoint controls, or SaaS security platforms.
• Knowledge of privacy-enhancing technologies or confidential computing.
• Contributions to AI/ML security research or community.

AI Resident – 2026 Cohort

The AI Residency Program is a full-time research opportunity designed to bridge the gap between academic research and industry applications in AI for materials science. Residents will work closely with Lila scientists and engineers on high-impact, open-science projects, with the option to focus on either fundamental or applied research.

• Duration: 6–12 months (extension possible)
• Start Dates: First hires beginning January 2026, with rolling applications and additional intakes in Summer and Fall 2026
• Cohort Size: Small group of selected residents
• Mentorship: Pairing with technical mentors, feedback from cross-functional teams
• Resources: Access to proprietary datasets, high-performance compute, and Lila’s research infrastructure

Research areas include ML-accelerated simulations, Bayesian methods, representation learning, generative models, agentic science, and ML-driven automation.

Your Impact at Lila

The Lila Sciences AI Residency is a full-time research program at the intersection of artificial intelligence and materials science. As a resident, you'll join a cohort of researchers tackling open-ended scientific challenges alongside Lila’s world-class team of scientists and engineers. With access to proprietary datasets, high-performance compute infrastructure, and experienced mentors, you'll pursue ambitious research projects with both academic and real-world impact. Publishing is encouraged but not required — what matters most is pushing the frontier of scientific discovery.

What You'll Be Building

• Design and execute independent research projects in AI for materials science
• Collaborate with Lila scientists and engineers on cutting-edge, open-science initiatives
• Explore domains such as ML-accelerated simulations, Bayesian methods, representation learning, generative AI, agentic science, and ML-driven automation
• Contribute to collaborative team research and co-develop novel approaches to scientific discovery
• Share findings internally and externally; publications are welcome but not mandatory

What You’ll Need to Succeed

• Degree in Materials Science, Chemistry, Computer Science, AI/ML, Physics, Mathematics, or related field (Bachelor’s, Master’s, or PhD)
• Proficiency in Python and deep learning frameworks (e.g., PyTorch)
• Experience working with large-scale datasets or simulations
• Familiarity with modern AI/ML architectures and training techniques
• Strong research background, demonstrated through publications, thesis work, or open-source projects

Bonus Points For

• Prior work on ML applications in scientific domains (e.g., materials discovery, chemistry, simulations)
• Familiarity with Bayesian optimization, active learning, or generative models
• Experience in reinforcement learning or agent-based approaches to scientific reasoning
• Open-source contributions or collaborative research experience
• Strong communication and writing skills, especially for conveying complex scientific ideas

Your Impact at LILA

Are you a strategic social thinker who thrives at the intersection of science, technology, and community? We’re seeking a Community & Ecosystem Growth Strategist who blends social strategy, influencer relations, and hands-on community building to accelerate Lila’s executives and scientific leaders’ credibility and reach. You’ll grow high-quality networks across academia, industry, government, and frontier tech ecosystems, helping our leaders participate credibly in technical discourse and earn durable attention.

What You’ll Be Building

Executive presence and follower growth

• Design and execute growth plans for key executives’ social profiles (X, LinkedIn, Substack, and niche platforms).
• Grow audiences with high-quality followers: researchers, lab leaders, R&D decision-makers, open-source contributors, and public-sector stakeholders.
• Establish an “always-on” cadence: posts, replies, threads, commentary, and light community engagement that feels authentic and valuable.

Engagement in frontier technical communities

• Actively participate in discussions around AI-accelerated science, robotics, materials science, life science, chemistry, frontier tech, generative AI, and agentic science.
• Bring Lila into conversations in helpful, credible ways, even in skeptical or high-signal threads.

Influencer and network activation

• Cultivate relationships with credible creators and technical influencers across academia, industry, and government-adjacent networks.
• Orchestrate co-created moments: AMAs, roundtables, briefings, interviews, guest threads, and research spotlights that elevate Lila leaders.

Thought leadership enablement

• Ghostwrite or co-author with executives and technical leaders while preserving their voice and cadence.
• Coach leaders on engaging in replies and threads to build trust and depth, not hype.

Measurement, learning, and iteration

• Define and track meaningful metrics: follower quality, engagement depth, network effects, and relationship development.
• Test hypotheses, and continuously refine the playbook.

What You’ll Need to Succeed

• Proven track record of organically growing executive and brand followings in technical/scientific spaces.
• Strong writing and editorial judgment for technical audiences; ability to translate complex ideas into clear, credible content.
• Comfort engaging in public technical discourse, including disagreement and skepticism.
• Marketing fluency to align with brand and communications strategy, plus the independence to run social/community initiatives day to day.

Bonus Points For

• Existing networks across AI-for-science, robotics, open-source, academia, national labs, or government-adjacent science/tech communities.
• Experience supporting executives or founders as thought leaders (voice, cadence, engagement strategy).

Your Impact at LILA

We are seeking a Product Marketing Manager, Physical Sciences to lead go-to-market for Lila’s AI-driven materials and chemistry platform. You will operate at the convergence of:

• Physical science domains: catalysts, sorbents, coatings, LNPs, quantum and extreme-environment materials
• Autonomous experimentation: flow chemistry ecosystems, high-throughput electrocatalysis, advanced characterization workcells
• AI & modeling: property prediction, design spaces, Bayesian optimization, LLM-augmented optimization

Your mission is to translate this tech stack into clear narratives, compelling launches, and credible evidence that resonate with:

• Industrial R&D and technology leaders in energy, chemicals, and manufacturing
• Sustainability and advanced materials teams
• Strategic partners, national labs, and federal programs

What You'll Be Building

Go-To-Market Strategy & Launch

• Define and execute GTM plans for new physical science capabilities (e.g., catalyst discovery campaigns, LNP property prediction, flow-reactor–based optimization, sorbents and coatings workflows), translating technical milestones into compelling market moments with clear offers, timelines, and success metrics.
• Translate PS product milestones (new AISF demos, CLUE campaign results, partner-ready vignettes) into launch-ready packages, including positioning, messaging, collateral, and enablement assets.
• Align launches with priority commercial motions in physical sciences (Accelerated By Lila, Lila Superscientists, joint development, and agentic science offerings) to maximize adoption and impact.

Messaging & Positioning

• Craft crisp, value-based messaging that communicates how Lila’s platform accelerates:
  • Catalyst and materials discovery for green hydrogen and electrochemistry
  • LNP design and advanced materials development for transport and separations
  • Coatings, sorbents, and quantum/extreme-environment materials discovery
• Tailor narratives for R&D executives, technical experts, and corporate innovation/sustainability leaders, clearly differentiating Lila from traditional HTE vendors, point-solution AI tools, and CROs.

Content Creation

• Produce technical and visionary content, including:
  • Domain-focused one-pagers and solution briefs (electrocatalysis, LNPs, sorbents, coatings, quantum materials)
  • Case studies and vignettes that translate CLUE campaigns, flow cell workcells, and AISF demos into partner-ready slides and visuals
  • Executive decks for Chevron, Merck-style conversations, industry keynotes, and joint partner briefings
  • Website and industry-page copy for physical sciences, in collaboration with Brand, CSO Materials, and PS leads

Sales & Field Enablement

• Partner with Commercial and BD to deliver high-impact collateral for physical-science prospects:
  • Pitch decks and talk tracks linked to CLUE, flow chemistry, LNP, sorbents, and coatings capabilities
  • Competitive positioning and objection handling against AI-for-materials and automation players
  • Simple ROI/value frameworks (faster time to best-in-class catalysts, improved yields, fewer experiments, enhanced durability)
• Capture learnings from customer and partner meetings (e.g., Chevron, energy majors, OEMs, national labs) and feed them back into messaging and product feedback loops

Market Intelligence & Insight

• Monitor competitive landscape and adjacencies in AI-driven materials discovery, HTE vendors, simulation platforms, and industrial R&D digitization
• Synthesize customer signals from commercial conversations, conferences (e.g., GTC, sustainability/energy events), and federal initiatives to inform PS product and business-model decisions
• Help prioritize PS storytelling priorities for 2026 (e.g., CLUE results and green hydrogen, LNPs and targeted delivery, extreme-environment coatings, quantum materials) to drive revenue and partnerships

Evangelism & Representation

• Serve as a visible advocate for Lila’s physical sciences work, supporting researchers in events, webinars, and joint partner sessions
• Collaborate with MarCom on PR and thought leadership that highlights CLUE, AISF for flow chemistry, electrocatalysis, carbon capture sorbents, and advanced materials achievements

Bonus Points For

Education

• Bachelor’s or Master’s degree in Chemistry, Materials Science, Chemical Engineering, or a related field. PhD a plus.

Experience

• 5+ years in B2B SaaS or technical product marketing, ideally within lab informatics, scientific software, or AI/ML for physical sciences, energy, or advanced materials.

Technical Understanding

• Strong grasp of AI/ML applied to physical sciences (e.g., property prediction, generative models for materials, Bayesian optimization, simulation-driven design).
• Comfortable discussing catalysis, sorbents, coatings, or related domains, even if you are not the domain PI.

Storytelling & Communication

• Proven ability to translate complex technical data and workflows into accessible, precise, and compelling narratives for scientists and business stakeholders; strong writing portfolio a plus.

Collaboration

• Track record of partnering with Product, R&D, and Commercial teams; able to serve as a trusted thought partner to PS leaders and researchers.

Execution & Ownership

• Strong project management skills; capable of coordinating multiple GTM streams in parallel and delivering on deadlines tied to events, partner meetings, and internal milestones.

Startup Mindset

• Comfortable in a fast-moving, highly cross-functional environment where product, category, and business models are evolving.

Your Impact at LILA

Your role in our Physical Sciences division will center on developing the next generation of in silico materials discovery methods, from creating autonomous workflows and data-driven pipelines to building the interface between simulation and AI. You’ll pioneer strategies that enable agents to reason over simulation data, extract latent insights, and guide hypothesis generation and materials design. Your work will expand how we leverage simulation outputs for discovery, accelerating the integration of physics-based modeling and AI reasoning systems. You’ll collaborate with experts in areas spanning simulation, AI agents, and experimental automation to push the boundaries of digital discovery.

What You'll Be Building

• Develop methods and workflows for in silico materials discovery that connect physics-based simulations, generative models, and agentic AI systems.
• Build intelligent pipelines where AI agents can design, launch, interpret, and refine simulations autonomously.
• Design frameworks that utilize simulation data more effectively for prediction, inference, and discovery, including automatic feature extraction, model training, and data-driven exploration.
• Prototype and evaluate new paradigms for simulation-aware agents that can learn from and act on scientific simulations.
• Design data representations, metadata standards, and APIs that enable seamless flow of information between simulations, machine learning models, and experimental databases.
• Create scalable, modular workflows that bridge electronic structure, atomistic, and mesoscale simulations with AI-driven reasoning and hypothesis generation.
• Collaborate with computational scientists, machine learning experts, and platform engineers to integrate in silico discovery pipelines into Lila’s broader scientific superintelligence ecosystem.

What You’ll Need to Succeed

• PhD or equivalent experience in Computer Science, Materials Science, Chemistry, Physics, Applied Mathematics, or related disciplines.
• Strong foundation in in silico materials discovery, computational materials modeling, and/or simulation workflow design.
• Familiarity with large language models and their application in scientific domains, and
• Experience building AI-driven or agentic workflows for scientific automation and discovery.
• Solid programming skills in Python and scientific computing frameworks
• Familiarity with atomistic simulation software and libraries (e.g., VASP, LAMMPS, ASE, Pymatgen, etc.).

Bonus Points For

• Strong publication record in in silico materials discovery, simulation-AI integration, AI-driven inverse design.
• Familiarity with scientific agent architectures, large-scale reasoning systems, or multi-agent frameworks for hypothesis generation and experimental planning.
• Familiarity with ontologies, metadata standards, and data infrastructure for scientific simulations.
• Experience with automated experiment–simulation loops, integrating computational predictions with robotic or cloud-based laboratory platforms.

Your Impact at LILA

Lila Sciences is seeking a highly skilled, hands-on Automated Systems Engineer to design, develop, and implement automation solutions across a broad range of laboratory workflows. Reporting to the Automated Systems Engineering Lead, this role is critical to building scalable, high-throughput automated workcells that translate scientific intent into reliable, real-world systems.

This role serves as a steward of scientific and cross-functional requirements—working closely with scientists, hardware, controls, and software teams to define scope, align interfaces, and drive projects from concept through deployment. The successful candidate will actively partner with scientific partners helping shape the technical direction of experimental automation in a fast-moving research environment.

What You'll Be Building

• Actively contribute to hands-on development, testing, and implementation of automated workflows in the lab.
• Develop scalable automated solutions for synthesis and characterization workflows, supporting a variety of material systems such as porous materials, catalysts, coatings, and advanced composites.
• Define and document standardized laboratory workflows, operating procedures, and system architectures to support reproducibility and scale.
• Lead and participate in equipment- and system-level FMEAs to improve robustness and operational safety.
• Assist in the troubleshooting and optimization of automated systems for throughput, reliability, and adaptability across diverse workflows.
• Design failure detection methods and maintain laboratory automation systems to ensure robust operations.

Project Innovation

• Translate scientific objectives into well-scoped technical requirements and automation architectures.
• Act as a connective tissue between science, hardware, controls, and software—ensuring interfaces are clear and solutions are cohesive.
• Explore and integrate emerging technologies, such machine vision, and advanced sensors, to enhance automation capabilities.
• Ensure alignment of automation solutions with safety, quality, and regulatory standards.

What You’ll Need to Succeed

• Strong hands-on experience developing and scaling automated workflows in laboratory or industrial settings.
• Understanding of Python programming, including API integration and error handling.
• Understanding of CAD design and rapid prototyping, including 3D printing.
• Hands-on experience with hardware systems, including electrical wiring, sensors, liquid/gas plumbing, and PID controllers.
• Strong critical thinking skills, attention to detail, and ability to work collaboratively in a dynamic environment.
• Excellent communication and interpersonal skills, with the ability to convey technical concepts clearly to diverse audiences.
• Familiarity with advanced experimental systems, including vacuum, laser, furnace, and electrochemical experimentation.
• Knowledge of machine vision applications and robotics control algorithms.
• Proven ability to integrate hardware and controls systems with automation workflows.
• Understanding of AI-driven decision-making in research automation.
• Prior experience leading technical teams in a fast-paced R&D environment.

Bonus Points For

Working at Lila Sciences, you would have access to advanced technology in the areas of:

• AI experimental design and simulation
• Automated custom instrumentation
• Generative molecular and material design

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 the Translational Sciences Team

We are building a dynamic drug discovery team in Boston, as part of Isomorphic Labs’ approach to transform how drugs are designed. Translational Sciences is an essential component of this effort, establishing and evolving our biological understanding of how to correct dysregulated systems in disease. This team will have impact across the full breadth of our portfolio, from critical input on target selection to essential partnership on biomarker development, to enable pharmacodynamic modulation and target engagement in the clinic.  Domain expertise will be critical to design translational strategies for programs, evolving our understanding of mechanisms and modes of action as programs progress.  This team will be highly collaborative and need to establish strong scientific relationships with multiple groups in the company, from Medicinal Chemists to Applied Machine Learning Scientists, creating a powerful symbiotic relationship that drives our internal and collaborative portfolios.

What you will do 

• Lead the preclinical Translational Science strategy in close collaboration with the Computational Biology, Preclinical Development and Translational Medicine teams, ensuring lifecycle-spanning screening cascades and biomarker assays are in place to guide programs toward clinical success.
• Ensure scientific rigor and "decision-quality" data across all local programs.
• Partner with the VP, Head of Drug Discovery, Cambridge, MA to recruit and retain a world-class team of scientists.
• Maintain a seamless collaborative loop with the Head of Translational Sciences, London to ensure resource sharing, protocol alignment, and unified scientific standards.
• Direct all in vitro and in vivo biology operations in Cambridge, MA through a network of CROs to generate, ingest and interpret high quality experimental data efficiently to support all aspects of our drug design programs from HitID through to IND.
• Foster a site culture of high accountability, rapid iteration, and scientific curiosity.
• Serve as a key internal consultant and advisor for global target discovery, providing critical technical assessment, feasibility analysis, and translational "stress testing" for new targets under consideration.
• Collaboratively execute program progression and determine resource allocation.
• Facilitate the transfer best practices and know-how between the UK and US sites to maximize R&D efficiency.
• Manage relationships with CROs and academic collaborators to extend the site’s internal capabilities.

Skills and qualifications 

Essential:

• PhD in relevant Biological Sciences.
• Solid foundation in Translational Sciences with a minimum of 10+ years previous industrial experience within a pharma/biotech/CRO setting, with a clear trajectory of increasing responsibility. 
• Proven track record of successfully navigating the discovery to IND transition, demonstrating mastery of molecular mechanisms.
• Track record of delivering multiple programs by formulating and implementing fit for purpose biological strategies to progress from hit ID through to IND as a program biology lead.
• Demonstrated experience in line management, mentorship, and developing scientific talent.
• Excellent strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Ability to work with computational biologists to define and implement patient and biomarker selection strategies
• Experience of working with and closely managing CRO resource. 
• Strong track record of scientific achievement, evidenced by publications, patents, and presentations.
• Genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.

Nice to have:

• Experience working in an AI/ML led drug discovery environment.
• Experience of  working with product /data scientist to build or configure data analysis systems for diverse  program datasets but specifically for pharmacological data.
• Experience of diverse chemical modalities e.g. molecular glues.

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.

Build Models Where None Exist Yet.

At Flagship Pioneering, we create companies from first principles. Within Flagship Labs, small founding teams define new technical theses, test them rapidly, and build ventures around breakthrough ideas.

We are forming a machine learning team inside a newly launched venture, Flagship Labs 120. Our work focuses on extracting latent structure from information-rich measurements of complex physical systems—often requiring mechanism-informed modeling, thoughtful inductive bias design, and principled approaches to inverse problems.

This is a zero-to-one role focused on modeling innovation rather than routine optimization. You’ll design, prototype, test, and refine new approaches that help define the technical foundation of a platform from day one.

What You’ll Do

• Develop and iterate on ML models for complex measurement data, from representation design through validation
• Design objectives and architectures that respect known constraints, symmetries, or latent structure in the data
• Explore and compare modeling strategies, balancing strong baselines with more experimental approaches when appropriate
• Investigate model behavior and failure modes to improve robustness and interpretability
• Collaborate closely with experimental and technical teammates to align modeling with data generation
• Contribute to shaping the long-term ML strategy and technical direction of a new venture

Who You Are

You may come from physics, applied mathematics, engineering, computer science, or another quantitative field.  You have hands-on experience developing machine learning models—ideally in deep learning, representation learning, probabilistic modeling, or related areas. You are comfortable implementing and modifying models, training them end-to-end, and working directly with real data.

You likely:

• Think algorithmically and reason from underlying structure
• Are comfortable adapting or extending model architectures when needed
• Have built and debugged meaningful ML systems or research prototypes
• Enjoy operating in dynamic, early-stage environments
• Read papers, build prototypes to test ideas, and translate concepts into working systems

What matters most is your ability to reason across data, models, and the systems they represent.

Technical Background

Required

• Strong hands-on experience building and training modern ML models
• Fluency in Python and at least one major ML framework (e.g., PyTorch or equivalent)
• Experience working with real-world or experimentally generated data
• Ability to design, run, and interpret ML experiments
• Comfort working in practical development environments (e.g., cloud infrastructure, experiment tracking, reproducible workflows)

Helpful

• Experience with inverse problems, latent-variable inference, or structured generative modeling (e.g., diffusion or flow-based methods)
• Familiarity with geometric or symmetry-aware architectures
• Experience incorporating physical or structural constraints into learning systems
• Experience working with time-series or high-dimensional signal data
• Exposure to biology, chemistry, physics, or related sciences

ABOUT FLAGSHIP PIONEERING

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

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

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

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

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

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

The salary range for this role is $130,000 - $230,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL120 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL120's good faith estimate as of the date of publication and may be modified in the future.

What if… you could join an organization that creates, resources, and builds life sciences companies that invent breakthrough technologies in order to transform health care and sustainability?

Company Description

Expedition Medicines is a privately held, early-stage biotechnology company pioneering the emerging field of Protein Editing. At Expedition Medicines we create small molecules that edit protein structure and function to unlock presently undruggable targets and a broad array of therapeutic modalities. Our platform integrates novel small molecule chemistry and chemoproteomic discovery technologies with Machine Learning (ML) to enable generative design. Expedition Medicines is backed by Flagship Pioneering, bringing their courage, vision, and resources to guide Expedition Medicines from platform validation to patient impact. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us! 

About the role:

The role of Senior/Principal Scientist, Structural Biologist will focus upon determination of protein-ligand complex structures by X-ray crystallography and cryo-EM.  The scientist in this position will be responsible for delivering structures and collaborating with project teams to enable structure-based drug design and elucidate the mechanism-of-action of small molecules. 

Candidate responsibilities:

• Design and execute structural biology strategy for one or more projects
• Oversee construct design, expression and purification of proteins for structure determination
• Develop and execute protocols to obtain high quality crystals for X-ray structures
• Develop and execute protocols for grid optimization, data collection, and data analysis for structure determination using cryo-EM
• Obtain and refine structures of protein-ligand complexes, communicate the results and collaborate with project teams to drive hit-to-lead and lead optimization
• Manage CROs for effective delivery of protein expression and structural biology services
• Expand our capabilities and serve as a trusted expert in structural biology

Qualifications:

• PhD/MS degree in structural biology, biochemistry, molecular biology, or a related field with at least 3 years of drug discovery experience in an industry setting
• In-depth knowledge and hands-on experience in X-ray crystallography and cryo-EM, including crystal optimization, grid preparation, data collection, data processing, structure refinement, and interpretation of protein structures
• Experience managing CROs for protein production and structural biology
• Excellent collaboration, communication, and organizational skills
• Strong desire to learn and implement new methods in protein biochemistry, biophysics, and structural biology
• Experience with biophysical methods (SPR, DSF, MST) or mass spectrometry (intact MS, peptide mapping, proteomics) is a plus

ABOUT FLAGSHIP PIONEERING

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

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

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

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

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

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

The salary range for this role is $126,000 - $214,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Expedition Medicines currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Expedition Medicines'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.

#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 the Computational Drug Design Team

We are building a dynamic team of Computational Chemists in Cambridge, MA within the Drug Design and Medical Research function. We drive the computational chemistry strategy for our internal portfolio and collaboration projects. Crucially, we partner closely with our AI/ML colleagues, using our domain expertise to augment the Isomorphic Labs Drug Design Engine and leverage its power to accelerate drug design. We foster a supportive, learning-focused environment where every member is valued, and continuous professional development is a priority.

Your Impact

As part of our expansion to Cambridge, MA, we are seeking an experienced and strategic Head of Computational Drug Design to join our foundational Drug Design team. This is a pivotal role for a motivated scientific leader eager to shape the future of drug discovery at the intersection of computational chemistry and artificial intelligence. This role requires a unique blend of deep scientific expertise and the ability to lead both technical projects and high-performing teams, whilst contributing to or leading active drug discovery programs.

You will provide scientific leadership and strategic direction for the Computational Drug Design team, responsible for delivery and guidance of projects to clinical candidate nomination. Additionally, you will oversee and mentor a team of talented Computational Drug Designers, fostering their scientific growth and career development. Working alongside world-leading AI Scientists, you will play a critical role in establishing principles for embedding AI/ML into modern computational chemistry workflows, ensuring seamless integration across ML, Biology, and Chemistry teams.  You will partner with our Head of Chemistry, Drug Design to champion the drug discovery pipeline, overseeing external collaborations (with CROs) and lead programs to deliver critical go/no-go milestones. Critical to this role will be the ability to build highly effective and efficient connectivity with Medicinal Chemistry, Biology and Pre-Clinical Development teams to accelerate pace to the clinic. If you are a skilled Computational Chemist with leadership experience and a passion for applying cutting-edge technology to complex scientific challenges, this role offers an unparalleled opportunity for impact and growth.

What you will do 

• Apply your knowledge and track record of modern drug design and discovery principles to deliver our Drug Design portfolio. 
• Provide direct line management for a growing team of Computational Chemists. Set clear goals, provide regular feedback, support their professional development, and foster a collaborative and high-performance team environment.
• Provide strategic input and technical direction to our AI/ML platform teams. 
• Collaborate both internally and with third party organisations, interacting within multidisciplinary teams, to support data-driven delivery of high quality scientific solutions to complex technical problems. 
• Represent the company externally, interacting with existing and prospective collaborators and Contract Research Organizations (CROs). 
• Prepare detailed scientific proposals and reports to support new and ongoing programs. 
• Embrace and champion our culture of inclusion and continuous professional development.

Skills and Qualifications

Essential:

• PhD in Computational Chemistry, Medicinal Chemistry, Synthetic Chemistry, or a related scientific field, or equivalent industrial experience.
• Solid foundation in computational chemistry with a minimum of 10+ years previous industrial experience within a pharma/biotech/CRO setting.
• Proven experience leading computational chemistry strategy and execution for multiple drug discovery programs and target classes, and managing high-performing scientific teams.
• Prior experience of leading drug discovery programs, from hit finding to lead optimisation and candidate selection.
• Strong expertise in virtual screening, ligand and structure-based drug design using physics-based and ideally AI/ML methods.
• Proven track record of developing models using ML or deep learning methods.
• Expertise in writing and implementing Python scripts for analysis and tool development, and/or utilising pipelining tools to support cheminformatics and design workflows.
• Genuine passion and enthusiasm for applying AI/ML to drug design and how this can transform the field.
• Demonstrated success managing external collaborations (industry/CROs) and working effectively in cross-functional environments.
• Growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Nice to Have:

• Prior experience leveraging machine learning and generative AI methods for hit finding (e.g. ultra-large virtual screening and active learning), molecular design and lead optimisation
• Strong knowledge of drug design principles, including ADMET and DMPK.
• Knowledge of modalities such as PROTACs, molecular glues, PPI inhibitors or ADCs.
• A track record of authorship of relevant scientific manuscripts.

About the Medicinal Drug Design Team

We are building a dynamic team of Medicinal Chemists in Cambridge, MA, to transform how drugs are designed. By partnering deeply with our AI/ML colleagues, we are doing more than just leveraging the Isomorphic Labs Drug Design Engine - we are actively shaping it. We use our domain expertise to challenge and refine our algorithms, creating a powerful symbiotic relationship that drives our internal and collaborative portfolios. Our team work closely together in a supportive environment, where everyone is valued for their medicinal chemistry expertise and experience they bring to the group. We have a strong growth mindset and prioritise continued development and learning.

Your impact 

As part of our expansion to Cambridge, MA, we are seeking an experienced and strategic Head of Chemistry, Drug Design to join our foundational Drug Design team. This is a pivotal role for a motivated scientific leader who is eager to shape the future of drug discovery at the intersection of medicinal chemistry and artificial intelligence. This role requires a unique blend of deep scientific expertise and the ability to lead both technical projects and high-performing teams, whilst contributing to or leading active drug discovery programs.

You will provide scientific leadership and strategic direction for the Medicinal Drug Design team, responsible for delivery and guidance of projects to clinical candidate nomination. Additionally, you will oversee and mentor a team of talented Medicinal Chemists, fostering their scientific growth and career development. Working alongside world-leading AI/ML Scientists, you will play a critical role in driving project success, enhancing our AI platform through expert feedback, and building a high-performing team. Critical to this role will be the ability to build highly effective and efficient connectivity with Computational Drug Design, Biology and Pre-Clinical Development teams to accelerate pace to the clinic. If you are a skilled Medicinal Chemist with leadership experience and a passion for applying cutting-edge technology to complex scientific challenges, this role offers an unparalleled opportunity for impact and growth.

What you will do 

• Apply your knowledge and track record of modern drug design & discovery principles to deliver our Drug Design portfolio. 
• Provide direct line management for a growing team of Medicinal Chemists. Set clear goals, provide regular feedback, support their professional development, and foster a collaborative and high-performance team environment.
• Provide strategic input and technical direction to our AI/ML platform teams. 
• Collaborate both internally and with third party organisations, interacting within multidisciplinary teams, to support data-driven delivery of high quality scientific solutions to complex technical problems. 
• Represent the company externally, interacting with existing and prospective collaborators and Contract Research Organizations (CROs). 
• Effectively manage CRO resource and monitor KPIs to maintain delivery. 
• Prepare detailed scientific proposals and reports to support new and ongoing programs. 
• Embrace and champion our culture of inclusion and continuous professional development. 

Skills and qualifications 

Essential:

• PhD in Synthetic Organic Chemistry, Medicinal Chemistry or a related technical field, or equivalent industrial experience.
• Solid foundation in medicinal chemistry with a minimum of 10+ years previous industrial experience within a pharma/biotech/CRO setting. 
• Proven track record of leading medicinal chemistry efforts on drug discovery projects, demonstrating significant contributions to project progression (ideally from Hit Identification through to Lead Optimization/Candidate Nomination, with familiarity of optimization of Drug Metabolism and Pharmacokinetics (DMPK).
• Demonstrated experience in line management, mentorship, and developing scientific talent.
• Excellent strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Strong strategic thinking, problem-solving, and decision-making capabilities applied to complex drug discovery challenges.
• Experience of working with and closely managing CRO resource. 
• Strong track record of scientific achievement, evidenced by publications, patents, and presentations.
• Genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.

Nice to have:

• Experience of successful application of fragment-based drug design approaches. 

About the team

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

About the role

In this role you will work on applying SOTA research and conduct your own research to develop novel methodologies to solve a large variety of challenging problems in Advertising related to conversion modeling aligned with attribution methodologies/models, calibration, dynamic creative generation and optimization, forecasting and timeseries modeling, yield and margin optimization and Experimentation for A/B and multivariate testing. 

We’re looking for a strong technical leader with a solid grasp of core statistical techniques and deep experience in SOTA Deep Learning discriminative and generative models. 

What you will be doing

• Applying existing and conducting your own research to build SOTA Deep learning discriminative models and build generative models to create image and video ads geared towards optimizing performance.
• Stay at the forefront of advancements in related areas. 

We're excited if you have

• PhD in quantitative disciplines such as CS, Statistics, Applied Math or a related field.
• Extensive experience in applied research using statistical and deep learning techniques.
• Published paper(s) on deep learning models for Advertising or related areas.
• Excellent communication and collaboration skills. 
• Experience in the Advertising domain (preferred)
• Contributions to open-source ML projects (preferred)

About the Team

At Roku, the UI team builds the foundational frameworks, tooling, and high-performance UI components that power experiences across millions of devices. We own the middleware and UI layers that enable smooth navigation, responsive interactions, rich animations, and consistent developer workflows across the platform.

Our work spans graphics rendering, layout and animation systems, performance optimization, and developer APIs that make it easy to create reliable, visually compelling applications at scale. We operate in a collaborative, high-trust environment and partner closely with firmware, platform, and product teams to ensure the end-to-end experience is fast, robust, and future-ready.

About the Role

As a Senior Software Engineer on the UI team, you’ll design, implement, and optimize systems that underpin Roku’s user experience and developer platform. You’ll work on performance-critical code paths across graphics rendering, animation, layout, and UI frameworks, ensuring smooth visuals and highly responsive interactions across a wide range of devices.

You’ll play a key role in shaping core architecture, working across the stack with hardware, firmware, and application teams, and delivering solutions that directly impact tens of millions of users. This role is ideal for engineers who enjoy deep technical problem-solving, care about performance at a systems level, and want to build the foundational layers that power great user experiences.

What You’ll Be Doing

• Build and scale UI frameworks and features optimized for millions of users
• Design and implement performance-critical systems across rendering pipelines, layout engines, and animation frameworks using C++
• Develop and maintain developer-facing tools and UI layers 
• Lead technical investigations and architect solutions across middleware and UI infrastructure
• Integrate AI/ML capabilities into developer workflows and platform features, leveraging generative AI to improve productivity and user experience
• Collaborate with cross-functional teams to deliver platform features with measurable gains in performance, reliability, and scalability
• Create tooling, frameworks, and automation that improve developer efficiency and code quality
• Mentor junior engineers through design reviews, pair programming, and technical guidance
• Stay current with advancements in graphics, UI systems, and AI, and proactively identify opportunities for improvement

We’re Excited If You Have

• 6+ years of software engineering experience with a strong focus on UI frameworks, systems, or application development
• Strong proficiency in C++ for performance-critical systems and rendering pipelines
• Strong proficiency in TypeScript for 
• Experience with Javascript/BrightScript or similar scripting languages
• Proficiency in Python for tooling, automation, or AI workflows
• Hands-on experience integrating AI/ML and generative AI tools into development workflows or product features
• Solid understanding of graphics systems, rendering, or UI performance optimization
• Strong debugging and root cause analysis skills
• Clear and effective technical communication skills
• A proactive mindset with a focus on continuous learning, fast iteration, and data-driven decision making

#LI-NM1

Why Join Us?

As a member of the Parabilis Medicines team, you will be a part of an organization dedicated to creating extraordinary medicines for diseases with urgent unmet needs, harnessing our proprietary peptide platform to transform treatment possibilities for patients. Parabilis is a clinical-stage biopharmaceutical company dedicated to unlocking high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. 

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and AR^ON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.

What’s the opportunity?

We are seeking a highly talented and self-motivated person to contribute to the development of the Computational Drug Discovery group, a strategic function in Data Science that is part of Parabilis’s platform discovery engine for HeliconTM stapled-peptide drugs.  The skill sets of the group includes state-of-the-art machine learning/generative AI, molecular modeling, cheminformatics and data science towards the discovery and development of HeliconTM stapled-peptide drugs.

You’ll be part of a data science team that is a central pillar of Parabilis’s innovative discovery platform and pipelines targeting “undruggable” genes of major therapeutic interest to patients. Our data science team is an integrated team, ranging from computational biology, bioinformatics, computational drug discovery, research informatics and engineering. We work at the interface of chemistry, biology, clinical and computational sciences, and are responsible for all aspects of data science, from building the discovery pipeline to supporting and developing our discovery .

Responsibilities

• Provide computational expertise towards, but not limited to, ternary complex designs for degraders and other proximity-based modalities, hit-to-lead progression using multi-objective optimization, initiating new projects, new drug-target assessments and advancing drug-pipeline projects towards the clinic.
• Identify, implement, and apply 3D modeling techniques for sampling HeliconTM peptide conformations in presence of a target, in ternary complex, and in different physiological environments.
• Analyze and derive 3D peptide-structure relationships.
• Exemplify scientific leadership by partnering across functions and working within a team of talented and passionate scientists to discover drugs.
• Interface with internal and external partners.

What you’ll need to be successful:

• PhD in Computational Chemistry, Protein Engineering, Chemistry, Physics, Macromolecular sciences or close-related field
• 5+ years of pharma/biotech industry experience in computational rational drug .
• Demonstrated experience with ternary complex design and understanding, peptide design or protein engineering and a good understanding of peptide structure-property relationships (e.g. helicity and amphiphilicity metrics, cell penetration).
• Demonstrated mastery of modern computational chemistry including, but not limited to, peptide folding and docking, use of co-folding foundation models, such as Boltz, structure-based design (receptor and ligand-based), scaffold hopping, docking and conformational analysis.
• An understanding of modern drug discovery including, but not limited to, medicinal chemistry, multi-parametric optimization, molecular recognition principles, and the ability to adapt and translate these principles to stapled peptides.
• Excellent communication and collaboration skills, with the ability to work well in a multidisciplinary environment
• Excellent organizational skills and attention to detail, with a strong passion for learning new concepts and technologies
• Expertise in one or more peptide modeling environments (e.g. ICM, Rosetta, Amber, GROMACS) and methods (enhanced sampling MD, Monte Carlo, MSM).
• Demonstrated understanding of critical assessment of molecule-property data and predictive model quality.
• Demonstrated understanding of experiments behind the data that can be translated to computational analysis.
• Experience with command line modeling applications.
• Familiarity with cloud computing environments.
• Strong scientific programming skills (Python) in a Linux environment.
• Experience with enterprise research informatics systems such as Dotmatics and chemical and biological data warehouses is a plus.
• Familiarity with concepts in machine learning.
• Familiarity with cheminformatics techniques is a plus.
• Familiarity with use of LLMs and IDEs, such as Cursor, to enhance workflows, productivity and innovation is a plus.
• Demonstrated use of AI tools in your current role and responsibilities is required. Advanced or innovated use of AI is a strong plus.

Core Values

Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent.We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused.We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In.We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary target for this position is $145,000 - $175,000 per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being.

As an equal opportunity employer, Parabilis values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

Warning: Fraudulent Job Adverts Beware of fraudulent activities claiming to represent Insurify. We are not associated with any entities soliciting personal information or payment. The safety of our job seekers is a top priority, and we actively work to prevent such incidents. Insurify will never request sensitive information or payment during the hiring process. Be cautious of text-only interviews, interviews conducted through Microsoft Teams, or suspicious offer letters. 

Why us? 

Insurify is one of America’s fastest-growing MIT FinTech startups and has been recognized as one of Inc. 5,000’s fastest-growing private companies in America in 2025, 2024, 2023, 2022 and 2021, Forbes Fintech 50 List for 2023, 2022, and 2021, Forbes Next Billion Dollar Startups of 2022 global and Top 100 InsurTech company. We’re changing the way millions of people compare, buy and manage insurance with artificial intelligence, technology, and superior product design.

Our company vision is to be recognized as the preeminent and most trusted digital agent for insurance comparison, purchase, and management. Our team is critical to achieving our vision and fostering the right culture is essential to our team’s success.

Join us if you like

• $1.3 Trillion market opportunity
• MIT alumni founders
• Female-led startup
• $130M total funding
• Strong leadership team with experience from many successful startups around the world

How you will make an impact

• Conduct keyword research and user intent analysis using SEO tools to create content outlines for transactional topics for writers and optimize existing content for both traditional search, AI Optimization (AIO), and Generative Engine Optimization (GEO).
• Partner on the ideation and execution of a scalable content strategy designed to grow qualified organic traffic while increasing visibility across AI-powered search experiences.
• Optimize on-page SEO elements including titles, meta descriptions, headers, internal linking, and structured content to improve rankings, click-through rates, and AI/LLM comprehension.
• Collaborate closely with SEO, editorial, and product teams to align content execution with evolving search algorithms, AI-driven search behavior, and business goals.
• Analyze SEO best practices, competitive landscapes, and performance data to identify and apply optimization opportunities, including content gaps and AIO/GEO-friendly formatting and coverage.
• Monitor and report on organic performance metrics such as traffic, rankings, CTR, and AI search visibility, using insights to continuously refine content and optimization strategies.

This is a hybrid position that requires candidates to be able to come into our Cambridge, MA office.

Who you are

• A self-starter with 1-2 years of experience in an SEO/Content role
• B.A./B.S. degree in Marketing, Communications, Business, Data Analytics, or Computer Science preferred
• Strong problem-solving skills
• Ability to navigate and execute in ambiguous problem spaces
• An understanding of how search engines and AI-driven ranking systems surface, interpret, and synthesize content across traditional and generative search experiences.
• Fast learner with the ability to quickly adapt to new tools and processes
• Strong project management skills
• Proactive and stays ahead of the latest search trends and algorithmic changes
• Excellent written and verbal communication skills
• Ability to work independently and as part of a team
• Excellent organizational and analytic skills
• Exceptional attention to detail
• Confident communicator with excellent presentation skills
• A team player with a solid work ethic
• Self-motivated and eager to keep learning and growing

Benefits

• Competitive compensation
• Generous stock options
• Health, Dental Coverages
• 401K plan with match
• Unlimited PTO
• Generous company holiday calendar
• Learning & Development Stipends
• Paid Family Leave
• Social impact volunteer time 
• Catered lunches in the office

Insurify is committed to offering a fair, competitive, and transparent compensation program that supports our mission to attract, retain, and motivate top talent. Our compensation philosophy is guided by several factors including a candidate’s relevant experience, education/training, job-related skills, and location.

In addition to the base salary our total compensation package includes health coverage, retirement contributions, and additional wellbeing benefits. Some positions may be eligible for company equity.

Below is the base compensation range for US locations:

$70,000-$80,000

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasizes teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Redwood City, CA:

• Senior Scientist I, Machine Learning: $257,400 - $330,000
• Senior Scientist II, Machine Learning: $290,900 - $373,000
• Principal Scientist, Machine Learning: $330,800 - $424,100

The salary range for San Diego, CA:

• Senior Scientist I, Machine Learning: $239,500 - $307,000
• Senior Scientist II, Machine Learning: $262,100 - $336,000
• Principal Scientist, Machine Learning: $312,100 - $400,100

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasises teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Senior Scientist I, Machine Learning: £115,600 - £152,100
• Senior Scientist II, Machine Learning: £131,900 - £173,500
• Principal Scientist, Machine Learning: £173,700 - £228,600

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute to Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Scientist I, Machine Learning: £74,900 - £98,500
• Scientist II, Machine Learning: £107,900 - £142,000
• Senior Scientist I, Machine Learning: £115,600 - £152,100

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source softwar

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

Warning: Fraudulent Job Adverts Beware of fraudulent activities claiming to represent Insurify. We are not associated with any entities soliciting personal information or payment. The safety of our job seekers is a top priority, and we actively work to prevent such incidents. Insurify will never request sensitive information or payment during the hiring process. Be cautious of text-only interviews, interviews conducted through Microsoft Teams, or suspicious offer letters. 

Why us? 

Insurify is one of America’s fastest-growing MIT FinTech startups and has been recognized as one of Inc. 5,000’s fastest-growing private companies in America in 2025, 2024, 2023, 2022 and 2021, Forbes Fintech 50 List for 2023, 2022, and 2021, Forbes Next Billion Dollar Startups of 2022 global and Top 100 InsurTech company. We’re changing the way millions of people compare, buy and manage insurance with artificial intelligence, technology, and superior product design.

Our company vision is to be recognized as the preeminent and most trusted digital agent for insurance comparison, purchase, and management. Our team is critical to achieving our vision and fostering the right culture is essential to our team’s success.

Join us if you like

• $1.3 Trillion market opportunity
• MIT alumni founders
• Female-led startup
• $130M total funding
• Strong leadership team with experience from many successful startups around the world

How you will make an impact

• Take the lead on designing, testing, and refining AI workflows and model configurations that produce engaging, accurate editorial content tailored to our brand’s unique voice.
• Edit, fact-check, and QA AI-generated content, ensuring every piece meets our high standards for relevance, helpfulness and clarity.
• Ensure AI content aligns with AP style and our proprietary style guides.
• Collaborate with editors, SEO team members, and cross-functional partners to manage complete content cycles, from ideation and content brief creation to publication, optimizing for user value and searchability.
• Own tracking of new AI tools, models, and innovations to position Insurify as an industry leader and innovator in ethical implementation of AI that helps our editors deliver the best value to our users at scale.
• Ideate, launch, and track AI experimentation aimed at continuous improvements and refinements of our workflow efficiency, content quality, and production.
• Partner with the Editor in Chief and editorial leadership to roll out new AI workflows to help the broader editorial team, including documentation, training materials, and best-practice guidelines.
• Train and coach editors and writers on AI tools and processes through live training, office hours, and 1:1 support, helping them confidently incorporate AI efficiencies into their processes.

This is a hybrid position that requires candidates to be able to come into our Cambridge, MA office three times per week.

Who you are

• A content strategist, writer or editor with at least 3 years experience in content creation.
• Experienced AI-wielder, adept with generative AI platforms, prompt engineering, and hands-on content editing.
• Proficient with SEO strategies and translating keyword data into real editorial improvements required.
• A passionate word-nerd with strong editorial judgment and a knack for making content genuinely helpful, trustworthy, and relatable.
• A patient teacher capable of helping your teammates implement new AI tools and strategies in their own work.
• A style devotee proficient with AP style, working with multiple brand style guides, and adapting (or even creating) editorial standards for digital audiences.
• A creative, collaborative professional who’s excited to work cross-functionally in a fast-moving, high-volume editorial environment and comfortable owning a new function within that environment.
• A bachelor’s or master’s degree-holder in journalism, English, communications, marketing, computer science, or related discipline.

Benefits

• Competitive compensation
• Generous stock options
• Health, Dental Coverages
• 401K plan with match
• Unlimited PTO
• Generous company holiday calendar
• Learning & Development Stipends
• Paid Family Leave
• Social impact volunteer time 
• Catered lunches in the office

Insurify is committed to offering a fair, competitive, and transparent compensation program that supports our mission to attract, retain, and motivate top talent. Our compensation philosophy is guided by several factors including a candidate’s relevant experience, education/training, job-related skills, and location.

In addition to the base salary our total compensation package includes health coverage, retirement contributions, and additional wellbeing benefits. Some positions may be eligible for company equity.

Below is the base compensation range for US locations:

$65,000-$75,000

About Sail:

Sail Biomedicines is pioneering the integrative design and deployment of fully programmable medicines to transform patient care. Sail’s platform combines first-in-class programmable circular RNA technology (Endless RNA™ or eRNA), and an industry-leading platform of programmable nanoparticles, utilizing natural components, to unlock comprehensive programming of medicines for the first time. By leveraging cutting-edge eRNA and nanoparticle deployment technology, Sail is building a wealth of data, enabling unparalleled use of generative AI techniques to identify and design fully programmable medicines that are potent, targeted, versatile, and tunable. Sail was founded by Flagship Pioneering.

The Role:

The Associate Director/Director of Clinical Supply Chain will be responsible for the strategic planning, execution, and oversight of end-to-end clinical supply operations across Sail’s clinical programs. This role will lead clinical supply strategy from first-in-human through late-stage trials, ensuring uninterrupted supply of critical materials, intermediates, products and finished good from/between suppliers through to clinical sites while maintaining regulatory compliance, cost control, and operational excellence. This position requires strong cross-functional leadership, hands-on execution capability, and deep expertise in global transportation logistics and clinical supply chain management within a biotech environment.

Responsibilities:

• Develop and execute clinical supply strategies for all clinical programs, aligned with clinical development plans and CMC timelines.
• Lead demand forecasting, supply planning, and inventory management
• Define packaging, labeling, and distribution strategies appropriate for trial design, geography, and regulatory requirements.
• Oversee clinical packaging, labeling, storage, and global distribution activities through CMOs, CPOs, depots, and logistics providers.
• Ensure timely availability of clinical supplies to investigational sites, minimizing risk of stock-outs or excess inventory.
• Manage external vendors (CMOs, packaging/labeling vendors, depots, couriers).
• Establish and manage contracts, budgets, KPIs, and performance reviews for supply chain partners.
• Serve as the primary supply chain interface with external manufacturing and logistics partners.
• Partner closely with Clinical Operations, CMC, Quality, Regulatory, and Finance to align supply plans with trial execution and regulatory strategy.
• Provide supply chain risk assessments and mitigation plans to program teams and leadership.
• Support clinical protocol development by advising on supply chain feasibility and complexity.
• Ensure all clinical supply activities comply with GxP, ICH, FDA, EMA, and global regulatory requirements.
• Support audits and inspections related to clinical supply operations.
• Author, review, and approve SOPs, plans, and supply-related documentation.
• Develop and manage clinical supply chain budgets, forecasts, and cost controls.
• Implement process improvements, digital tools, and best practices to enhance efficiency and scalability.
• Build and scale clinical supply chain capabilities as Sail’s pipeline grows.

Required Qualifications:

• Bachelor’s degree in Supply Chain, Life Sciences, Engineering, or a related field (advanced degree preferred).
• 8+ years of direct experience in clinical supply chain, pharmaceutical supply chain, or related roles in biotech/pharma.
• Proven experience supporting Phase 1–3 clinical trials, including global studies.
• Strong knowledge of GxP, clinical packaging/labeling, and global distribution requirements.
• Demonstrated ability to manage external vendors and complex cross-functional projects.
• Excellent communication, problem-solving, and leadership skills.
• Demonstrated experience managing global clinical supply chains for multiple chemical and biological entities.
• Experience in a clinical-stage or high-growth biotech environment.

Preferred Qualifications:

• Experience driving clinical supply chain operations.
• Familiarity with IRT/RTSM systems and clinical supply forecasting tools.
• Experience supporting regulatory inspections and audits.
• Technical background in clinical or commercial manufacturing of multiple therapeutic modalities i.e. small molecules, ADC and biologics

Salary Range: $175,000 - $240,000

Sail Biomedicines is an Equal Opportunity Employer. Sail does not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, national origin, veteran status, or any other status protected under federal, state, or local law.