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

Your Impact at LILA

Lila Sciences is seeking Platform Scientists, Soft Materials Focus to ideate, prototype, and transfer new experimental concepts for AI Science Factories targeting complex and soft material systems. In this role, you will work at the forefront of scientific ideation—partnering with a broad range of chemistry, materials, and AI teams to define new approaches to formulation, structure–property relationships, and performance evaluation. You will translate these concepts into scalable experimental workflows, custom apparatus, and software-enabled systems for autonomous research.

What You'll Be Building

• Collaborate with diverse scientific teams to ideate new experimental strategies for soft and complex materials, including formulations, colloids, polymers, gels, and biological or hybrid systems
• Lead conceptual development of characterization and performance workflows leveraging techniques such as SAXS, SANS, rheology, and formulation performance assays
• Design, prototype, and validate custom apparatus, experimental methods, and software tools to realize these concepts
• Develop and refine workflows that connect structure, dynamics, and performance across multiple length and time scales
• Transfer successful prototypes into production-ready systems within Lila’s AI Science Factory platform, enabling autonomous experimentation

What You’ll Need to Succeed

• MS or PhD in Materials Science, Chemistry, Chemical Engineering, Physics, or a related field, with a focus on soft or complex materials
• Demonstrated experience collaborating across scientific disciplines to generate and refine experimental concepts
• Hands-on experience with one or more of the following: SAXS, SANS, rheology, formulation performance or functional assays
• Experience designing and implementing custom experimental workflows and/or scientific software
• Strong programming skills (e.g., Python, C++, or similar) applied to data analysis, automation, or experiment control
• Excellent communication skills and comfort operating in a fast-paced, exploratory R&D environment

Bonus Points For

• Experience with lab automation, high-throughput experimentation, or instrument control software
• Background in formulation science (e.g., consumer products, coatings, energy materials, bio-soft matter)
• Experience linking scattering, rheological, and performance data to predictive or ML-driven models
• Familiarity with prototyping tools such as 3D printing, machining, microfluidics, or custom sample environments
• Industry or national lab experience working on soft materials or complex fluids

Your Impact at LILA

As a Machine Learning Scientist focused on Scientific Reasoning, you will help pioneer the next generation of AI systems capable of reasoning like a scientist. You’ll design novel frameworks that push the boundaries of LLM-based reasoning methods — while also implementing scalable frameworks that integrate with Lila’s platforms. This role bridges deep theoretical thinking with practical ML engineering, enabling breakthroughs in how scientific hypotheses are generated, tested, deployed and optimized.

What You'll Be Building

• Design and formalize frameworks for scientific reasoning with LLMs, including structured prompting, reasoning chains, and test-time compute.
• Explore and implement methods for in-context learning, self-reflection, and adaptive reasoning in scientific discovery workflows.
• Build scalable model prototypes that can be deployed to solve frontier scientific problems.
• Collaborate with scientists and engineers to encode domain knowledge into reasoning systems that integrate symbolic and statistical approaches.

What You’ll Need to Succeed

• PhD (preferred) or equivalent research/industry experience in Computer Science, Machine Learning, AI, Engineering, Materials Science or related fields.
• Strong programming skills in Python with deep expertise in LLM frameworks (PyTorch, HuggingFace Transformers, LangChain, LlamaIndex, and related toolkits).
• Expertise in LLM reasoning methods: in-context learning, test-time compute, chain-of-thought, or tool-augmented reasoning.
• Ability to balance theoretical research with practical ML engineering to deliver scalable solutions.

Bonus Points For

• Research experience in causal reasoning, symbolic AI, or probabilistic programming.
• Contributions to open-source LLM reasoning frameworks.
• Familiarity with scientific discovery pipelines in chemistry, biology, or materials science.
• Experience with multimodal reasoning (e.g., combining text, image, and experimental data).
• Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, ACL).

COMPANY DESCRIPTION

Flagship Pioneering is a bioplatform innovation company that invents and builds companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health, sustainability and beyond exponentially accelerate scientific progress in areas ranging from disease detection and treatment and nature-positive agriculture to novel applications of AI that are driving the creation of new technologies.   

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

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

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

THE ROLE

We are seeking a Senior Machine Learning Scientist, Climate and Hydrology to lead the scientific direction and machine learning development for hydrology-aware climate modeling within our broader environmental modeling platform.

This role sits at the intersection of hydrology, weather and climate science, and large-scale machine learning. The Sr. Scientist will help shape how hydrologic process understanding, climate data, and modern ML methods are brought together in next-generation prediction systems, with emphasis on scientifically grounded model development and evaluation.

The individual in this role will work across science, ML, engineering, and data teams to define research priorities, guide model training and benchmarking, build reproducible workflows, and translate scientific insight into scalable model development. This is a cross-functional role requiring strong technical depth, structured scientific thinking, and the ability to move between foundational research and applied execution.

KEY RESPONSIBILITIES

• Lead scientific and technical efforts at the intersection of hydrology, climate science, and machine learning.
• Help define research priorities, modeling directions, and evaluation strategies for next-generation climate and environmental prediction systems.
• Contribute to the development and improvement of ML-based modeling approaches informed by physical and Earth system science.
• Work with large-scale climate, weather, hydrology, and remote sensing datasets to support model development and scientific analysis.
• Build and oversee reproducible workflows for data processing, model training, benchmarking, and validation.
• Collaborate closely with research, engineering, and data teams to translate scientific goals into scalable technical execution.
• Guide assessment of model performance, uncertainty, and scientific robustness across a range of environmental conditions and applications.
• Communicate findings through internal reviews, external collaborations, publications, and technical presentations.
• Help shape the broader scientific roadmap and contribute to team growth and cross-functional leadership.

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• PhD in machine learning, computational science, Earth science, atmospheric science, hydrology, AI, computer science, or a related quantitative discipline.
• 5+ years of postdoctoral, industry, or applied research experience in climate ML, weather ML, hydrologic modeling, Earth system modeling, or a closely related field.
• Demonstrated experience with ML-accelerated weather, climate, or hydrology models, with a strong publication track record in the area.
• Experience working with large climate datasets, including reanalysis products, remote sensing datasets, observational datasets, and model output.
• Experience with the computational infrastructure required to manage, preprocess, and train on large-scale climate datasets, preferably in the AWS ecosystem.
• Strong programming skills in Python and experience with modern ML frameworks such as PyTorch
• Background in scientific ML, spatiotemporal modeling, data assimilation, hybrid physics-ML methods, or related approaches is strongly preferred.
• Ability to design rigorous evaluation frameworks, performance metrics, and benchmarking approaches for environmental prediction systems.
• Strong technical writing and communication skills, including reports, presentations, and peer-reviewed publications.
• Demonstrated ability to work independently in fast-paced, ambiguous environments while collaborating effectively across disciplines.
• Experience leading cross-functional scientific efforts, mentoring researchers, or helping define research roadmaps is preferred.

LOCATION: Cambridge, MA or Boulder, CO (some travel to Cambridge, MA based headquarters if working from Colorado)

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-TL1

The salary ranges for this role are $127,000 - $205,900 (Colorado) and $168,000 - $231,000 (Massachusetts). Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Protocos currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Protoco's good faith estimate as of the date of publication and may be modified in the future.

About Graphcore

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

Job Summary

As a researcher at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialised hardware has been the key driver of the progress of AI over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this exciting field. As such, we’re looking for candidates who are keen scientists and engineers, with the theoretical and practical skills needed for impactful AI research.

We are looking for researchers with experience of AI in low-power, edge and embodied scenarios such as robotics, autonomous driving and augmented/virtual reality. We are interested in the training and deployment of multimodal AI models in these contexts, covering areas such as world models, real-time computer vision, generating and reasoning over audio/video streams.

The Team

Graphcore Research participates in both fundamental and applied research, to characterise the computational requirements of machine intelligence and to demonstrate how hardware can drive the next generation of innovative AI models. We publish at leading AI/ML conferences (NeurIPS, ICML, ICLR) as well as specialist workshops, and collaborate with other research teams and organisations across the world.

We pride ourselves on being a supportive and collaborative team, where we organise around our individual research interests to solve problems together in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications, including for sequence- and graph-based data. We’re based across London, Cambridge and Bristol, with projects and discussions that involve all our locations.

Perhaps the best way to get an idea of what we’re all about is to read one of our papers or an article on our blog. If you’re excited to work at the cutting edge of AI supported by new hardware and want to develop your skills in this area, we’d love to hear from you!

Responsibilities and Duties

• Generate AI/ML ideas, design experiments, implement them & evaluate results.
• Prepare, submit & present your work to AI conferences and workshops.
• Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware.

About you:

Essential:

• Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering).
• Experience in embodied AI, world models or robotics.
• Python programming in a modern deep learning framework, e.g. PyTorch or JAX.
• Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling.
• Capable of designing, executing and reporting from ML experiments.
• Mathematics skills to support the above: calculus, probability theory and linear algebra.
• Experience submitting papers to international scientific conferences or workshops.

Desirable:

• Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton.
• Practical familiarity with hardware capabilities for deep learning – threads, caches, vector & matrix engines, data dependencies, bus widths and throttling.
• Practical familiarity with software stacks for deep learning – compilation, kernel fusion, XLA/ATen ops, streams, and asynchronous execution.
• Conference or workshop submissions in the fields of embodied AI, world models, or robotics.

Benefits

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

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

MORSE is searching for an experienced Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will be part of teams performing Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Perform data analysis, test and evaluation of existing machine learning algorithms, and development of advanced algorithms to model physical and autonomous systems,

• Work with MORSE’s current team of engineers to transition algorithms to software applications and real-time embedded systems.

• Support the transition of the developed algorithms to software using one or more programming languages such as Python, C, C++, Java, or MATLAB.

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Research and identify new methods for machine learning and data analysis

Requirements:

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

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 5+ years of experience in Data Science or Analysis

• Solid understanding of data analysis, physics, linear algebra, statistics, algorithms, optimization, and/or machine learning methods

• Proficiency in one or more programming languages like Python, Matlab, C, or C++

• Demonstrated experience with large, multidimensional, or complex data sets in one or more of the following areas: parsing, cleaning, storage strategies, provenance tracking, database formats, and parallelized data transformations

• Good communication skills

• Self-starter and driven

• Prior experience in defense is a plus

MORSE is searching for a Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will be part of teams performing Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Perform data analysis, test and evaluation of existing machine learning algorithms, and development of advanced algorithms to model physical and autonomous systems,

• Work with MORSE’s current team of engineers to transition algorithms to software applications and real-time embedded systems.

• Support the transition of the developed algorithms to software using one or more programming languages such as Python, C, C++, Java, or MATLAB.

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Research and identify new methods for machine learning and data analysis

Requirements:

• US CITIZENSHIP REQUIRED and an active Top Secret Security Clearance with SCI eligibility 

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 3+ years of experience in Data Science or Analysis

• Solid understanding of data analysis, physics, linear algebra, statistics, algorithms, optimization, and/or machine learning methods

• Proficiency in one or more programming languages like Python, Matlab, C, or C++

• Demonstrated experience with large, multidimensional, or complex data sets in one or more of the following areas: parsing, cleaning, storage strategies, provenance tracking, database formats, and parallelized data transformations

• Good communication skills

• Self-starter and driven

• Prior experience in defense is a plus

MORSE is searching for a Lead Data Scientist with expertise in data analysis, data science, and algorithm development in one or more of a variety of fields including visual classification, big data, natural language processing, machine translation, time sequenced data, and advanced metrics. You will lead teams and strategy for Algorithm Test and Evaluation (T&E) of AI and machine learning models and algorithms to give national security customers insights into the capabilities of applying AI to solve real world problems.

Responsibilities:

• Define goals and expectations for algorithm T&E performance

• Research artificial intelligence data splitting, metrics, and T&E methodology

• Lead strategy and coordination with algorithm development vendors

• Work with customers, stakeholders, and other vendors to present concepts, analyses, and test results

• Present a path forward and solutions to solve complex data problems

• Work with MORSE’s current team of engineers and scientists to transition algorithms to software applications and real-time embedded systems.

Requirements:

• US CITIZENSHIP REQUIRED and an Active Top Secret U.S. Security Clearance with SCI eligibility (TS/SCI) 

• Masters or Ph.D in Data Science, Computer Science, Engineering, Applied Mathematics, Physics, Physical or Biological Sciences or a related field

• 7+ years of experience in Data Science, Artificial Intelligence, or Machine Learning

• Expertise in artificial intelligence, machine learning, and data science 

• Experience in algorithm development and testing

• Excellent communication and presentation skills

• Self-starter and driven

• Ability to be onsite 4-5 days/week 

Your impact at LILA

We’re building a talent-dense, high-agency research team to develop the next generation of learning systems and reasoning algorithms for agentic LLMs. Our work sits at the intersection of large language models, post-training, and scientific reasoning, with the goal of enabling systems that learn from experience, reason effectively, and improve through interaction.

Scientific domains present a distinct set of challenges that make this problem uniquely hard. Feedback is sparse and delayed — experiments take days or weeks, not milliseconds. Ground truth is expensive or contested. Distribution shift is structural, as instruments, techniques, and knowledge bases evolve continuously. The hypothesis space is vast and reward signal is thin. Existing benchmark do not capture these nuances. The goal is to build systems that can operate effectively in this scientific regime.

This role spans a few complementary directions. Candidates are expected to bring deep expertise in one (ore more) of the following areas. In the event of cross-track expertise, please select the one you align to the most. Our interview process will be catered to verifying the chosen expertise area.

Expertise Area 1 — Agentic system building

Focus: Build systems that autonomously propose, execute, and verify scientific hypotheses over long time horizons.

• Create and analyze long-running auto-research systems that propose and verify hypotheses
• Design planning frameworks for agentic systems operating over long, sparse feedback loops
• Design memory architectures that allow agents to build and retrieve structured knowledge over time
• Explore algorithms in recursive self-improvement, multi-agent coordination, and continual learning

Expertise Area 2: Distillation

Focus: Translate strong inference-time behaviors and reasoning traces into efficient, trainable models.

• Develop distillation strategies from large or ensemble models into deployable systems
• Research methods for self-improvement, including iterative self-distillation and critique loops
• Investigate how to preserve generalization and reduce catastrophic forgetting through the distillation process

Expertise Area 3 — Scalable experience generation

Focus: Develop inference-time algorithms and synthetic data pipelines that generate high-quality training signal for scientific reasoning.

• Design and benchmark inference-time search, sampling, and verification strategies
• Propose new techniques in synthetic environment creation and curriculum learning
• Develop synthetic data generation strategies that capture high-quality scientific reasoning for agentic model training
• Measure the end-to-end impact of inference-time improvements on real scientific tasks

What you’ll need to succeed:

• An advanced degree in computer science, machine learning, or a related field, or or comparable experience
• Strong foundation in LLMs and empirical research
• Experience designing and executing rigorous ML experiments, including benchmarking and ablations
• Experience working with large-scale training or evaluation pipelines
• Ability to define and pursue research directions in open-ended, rapidly evolving spaces
• Strong collaboration and communication skills across research and engineering teams

Bonus points for:

• Experience with synthetic data generation, distillation, or self-improvement loops
• Familiarity with reinforcement learning (e.g., RLHF, on-policy methods)
• Experience with planning, search, or decision-making systems at scale
• Experience in building agentic systems with tool use, or multi-agent workflows
• Background in program synthesis, coding benchmarks, or long-horizon tasks
• Experience building evaluation frameworks or large-scale benchmarks

Scientific rigor & persistence:

• You take a principled approach to experimentation, with careful baselines, ablations, and evaluation design
• You are motivated by understanding why systems work, not just improving metrics
• You prioritize clarity, reproducibility, and intellectual honesty in research
• You are comfortable working through long, nonlinear iteration cycles
• You operate effectively in ambiguous, fast-evolving research environments

Company Overview:

PhaseV (HQ in Boston, R&D in Tel Aviv) is a cutting-edge startup, pushing innovation in the drug development process to bring new treatments to more patients, in a more efficient and precise way. Leveraging the power of advanced causal inference and pushing the boundaries of machine learning, PhaseV detects hidden signals in clinical data and extracts actionable insights for planning the optimal trial. The company's proprietary ML-based platform for adaptive clinical trial design and closed-loop execution enables sponsors to easily and quickly unlock the potential of adaptive clinical trials, reveal the optimal adaptive design to meet their trial objectives and execute more efficient, more precise, and more successful clinical trials. Collaborating with 7 of the top pharmaceutical companies, as well as multiple CROs and biotechs, we are poised to make a significant impact on how drugs are developed and brought to market.

Position Overview:

We are seeking a talented Data Scientist to join our team of researchers. The ideal candidate will have a strong foundation in machine learning and statistics with an interest in causal inference. A couple of recent preprints we’ve released to get a sense of the challenges:

• Causal Responder Detection (https://arxiv.org/abs/2406.17571)
• Robust CATE Estimation Using Novel Ensemble Methods. (https://arxiv.org/abs/2407.03690)

Key Responsibilities:

Technical Development:

• Implement and optimize ML algorithms, with a focus on causal ML applications in clinical trials
• Collaborate with senior data scientists to develop and improve our analytical platforms
• Work alongside clinical and biological experts to translate complex problems into technical solutions

Research & Analysis:

• Conduct rigorous statistical analyses of both randomized and observational data
• Develop and validate methods for responder identification and treatment effect estimation
• Document and present methodologies and results for internal and external stakeholders

Collaboration:

• Work cross-functionally with engineering and product teams
• Contribute to technical discussions and peer code reviews
• Support the preparation of technical documentation and research papers

Qualifications:

Education:

• Master's in Computer Science, Statistics, Data Science, Engineering or a related field
• Ph.D. is an advantage but not required

Experience:

• 3+ years of experience in data science or machine learning roles
• Experience with ML in a practical research or industry setting
• Background in statistical modeling and analysis

Skills:

• Strong programming skills in Python (R in addition - an advantage)
• Proficiency in statistical analysis and machine learning
• Experience with data visualization and communication of technical concepts
• Strong analytical and problem-solving skills

Preferred:

• Familiarity with causal inference concepts
• Experience in healthcare or biotech industry
• Experience with large-scale data processing

What We Offer:

• Join us on a mission to bring more effective drugs to more patients.
• The opportunity to work with an amazing team passionate about making a real-world impact.
• Extremely hard and diverse problem setting, in which the team is pushing the envelope.
• A collaborative and dynamic startup environment.
• Professional growth and development opportunities.

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

• Design and develop autonomous robotic systems for transport and workcell operations, integrating advanced path planning, navigation, and motion planning algorithms
• Build production-grade mobile manipulation platforms leveraging ROS/ROS2 and modular robotic architectures
• Advance robotic perception by integrating sensing modalities such as 3D vision, LIDAR, and tactile sensors to enable robust, adaptable task execution
• Use simulation environments to model, test, and optimize task planning, scheduling, and robot behaviors in diverse lab scenarios
• Collaborate with AI, mechanical, and software engineering teams to translate theoretical robotics research into real-world autonomous systems

What You’ll Need to Succeed

• Ph.D. in Robotics, Computer Science, Mechanical/Electrical Engineering, or a related field, or equivalent research experience
• Expertise in motion planning, path planning, and navigation for manipulation and mobile robotics
• Proficiency with ROS/ROS2, C++, and Python, with hands-on experience building robotic systems in real-world environments
• Deep understanding of perception systems and sensor integration (e.g., camera, LIDAR, tactile sensors)
• Proven ability to take robotic systems from concept through to deployment

Bonus Points For

• Experience with dual-arm mobile manipulation systems or other high-DOF robotic platforms
• Familiarity with simulation tools such as Gazebo, Isaac Sim, or PyBullet
• Background in machine learning for perception, control, or adaptive planning
• Experience with real-time decision-making in human-robot collaboration scenarios
• Strong publication or patent record in robotics, autonomy, or perception

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

The Role:

Reporting to the Head of PV Science, the Associate Director, Drug Safety and Pharmacovigilance Scientist is responsible for assessing and interpreting safety data from multiple sources, including clinical trials, spontaneous and solicited reports, aggregate, and literature reports. This individual is expected to provide interpretation and summaries of drug safety information and provide input in the generation of safety reports (e.g., DSURs, PADERs, PBRERs, and clinical safety assessments). This individual may also support the medical assessment of Individual Case Safety Reports (ICSRs) and other drug safety information. The individual will be an integral part of a group of safety professionals within Nuvalent and will closely collaborate with safety teams in Contract Research Organizations (CROs) and partners. He/she will need to maintain medical knowledge as required by the role, strong and current knowledge of drug safety and pharmacovigilance regulations, pharmacovigilance practices, safety surveillance and risk-management practices.

Responsibilities:

• Contribute to the generation of aggregate safety reports including development safety update reports, periodic benefit risk evaluation reports, and provide medical input in review of new or existing safety documents to ensure compliance with relevant regulatory requirements, such as protocols, safety summaries and regulatory reports
• Contribute to signaling and safety surveillance processes, including the identification of safety observations, emergent safety concerns and new safety signals, ensure prompt assessment and communication of confirmed safety signals
• Serve as a medical resource for the generation and review of clinical trial protocols, informed consent forms (ICFs) and investigator brochures (IBs) and the development of Reference Safety Information
• Contribute to creation or and updates to Risk Management Plans (RMPs) and/or Risk Evaluation and Mitigation Strategies (REMS) and the maintenance of these documents
• Contribute to the development of Standard Operating Procedures, Working Instructions and other guidance documents
• Provide safety and pharmacovigilance training programs as required
• Collaborate cross functionally (e.g., Reg Affairs, Clin Ops, Clin Science) to ensure pharmacovigilance input
• Support the medical assessment of ICSRs as needed
• Support other pharmacovigilance and drug safety responsibilities as assigned

Competencies Include:

• Design global risk management frameworks for Nuvalent’s medicines
• Translate safety data into clinical insights
• Adapt visualization tools for safety surveillance
• Influence multidisciplinary teams to prioritize patient safety.
• Strong ability to build relationships, collaborate and influence across disciplines within Nuvalent and with outside stakeholders

Qualifications:

• 4+ years’ experience in Drug Safety / Pharmacovigilance in a pharmaceutical or biotech company, CRO or regulatory agency
• 7+ years of Pharma / CRO experience. 
• Degree in a medical or healthcare related discipline like MD, PharmD, RN or PhD.
• Excellent knowledge of US and EU drug safety regulations, CIOMS and ICH guidelines
• Experience with medical drug safety assessments, drug safety surveillance and monitoring activities
• Experience with safety data collection and interpretation from clinical trials, literature and post market
• Experience with preparation of responses to Regulatory Authorities and experience with IND/NDA submissions and negotiations with Regulatory Authorities as part of marketing approval
• Experience with the development and updates to Reference Safety Information, IB, Company Core Data Sheet and local labels
• Excellent verbal, written and presentation skills

Additional Information:

Nuvalent is committed to fair and equitable compensation practices, aiming to provide employees with competitive total rewards packages.

The targeted salary range reflects what Nuvalent reasonably and in good faith expects to offer for this position at the time of posting, but the final salary determination may be within or outside this range based on various factors, including, but not limited to, experience, skills, education, and market factors.  The range will be reviewed regularly and is subject to change.

Nuvalent also offers a comprehensive benefit package to support our employees at each stage of their career, financial, health, and well-being journey, including medical, dental, and vision insurance, 401(k) retirement savings plan, generous paid time off (including a summer and winter company shutdown), and much more.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Design and build capability evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs, across biological / physical sciences.
• Coordinate and lead threat modelling exercises with internal and external scientific experts, including monitoring for emerging technologies and use-cases.
• Develop and curate high-quality training and test data for evals and safety systems.
• Evaluate risks from Lila’s capabilities, including through interactions with the wider ecosystem of capabilities (e.g. general-purpose frontier models as well as narrow scientific tools)
• Contributing to broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.
• Contribute to external communications on Lila’s safety efforts.

What You’ll Need to Succeed

• A PhD in either a biological sciences domain (e.g., molecular biology, virology, computational biology or related fields) or a physical sciences domain (materials sciences, physics, chemistry, chemical or nuclear engineering, or related fields), or other related experience.
• Experience in scientific computing, across either biological or physical sciences.
• Familiarity with dual-use research and dissemination concerns, across the relevant safety / regulatory / governance frameworks (e.g. export control frameworks, biological and chemical-related conventions and controls).
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.
• Demonstrated ability to lead teams of internal and external collaborators in buildout of Lila’s point-of-view on biological / physical risks
• Demonstrated ability to deal with cross-functional stakeholders (science, AI, product, policy) in a complex environment.

Bonus Points For

• Experience in developing or applying ML to biological or physical sciences
• Experience in building evaluations, or conducting red-teaming exercises, across scientific risks for frontier models / narrow scientific tools.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

• For US-based candidates (Cambridge or San Francisco), we expect the base salary for this role to fall between $176,000–$304,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.
• For UK-based candidates, compensation will be determined separately and will be aligned with local market benchmarks and internal leveling.

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

We are seeking a Scientist (II) to join our Physical Sciences team. This role will focus on assisting in the design and development of a high throughput chemical synthesis platform, with emphasis on medicinal chemistry and drug delivery applications. The ideal candidate will have experience synthesizing, analyzing, and optimizing novel molecules to build out structure-activity relationships for a library of compounds. This position will work closely with others across the chemistry, formulations, engineering, machine learning, and data science teams to help establish next-generation tools for therapeutic development and drug delivery. Your work will bridge the physical sciences and bioanalytical domains, enabling high-throughput experimentation for closed-loop optimization of organic compounds.

What You'll Be Building

• Design, synthesize, and optimize novel lipids, small molecules, and other combinatorial chemistry compound libraries for drug delivery applications
• Design and deploy high-throughput synthesis strategies, build automated assay platforms, and develop innovative approaches to interrogate large chemical spaces
• Partner closely with chemistry, computational, and automation teams to establish structure-activity relationships for compound libraries to guide iterative design strategies
• Implement data-driven approaches to analyze screening outputs and guide iterative molecule design.
• Work with and manage projects with CDMOs for research-grade synthesis, with considerations towards scale-up of lead compounds
• Establish best practices for screening data quality, reproducibility, and assay robustness.
• Collaborate across disciplines to translate screening hits into validated chemical starting points for therapeutic programs.

What You’ll Need to Succeed

• Ph.D. in Chemistry, Chemical Engineering, or a related field.
• ≥ 1 years of experience with automation, instrumentation, and integrating real-time analytics into experimental workflows.
• Strong background in organic synthesis, with experience designing and synthesizing novel organic compounds.
• Excellent problem-solving, communication, and collaboration skills.

Bonus Points For

• Familiarity with novel lipid design for drug delivery applications
• Prior knowledge and implementation of biodegradability and tolerability design principles, with working knowledge of biological implications of compound moieties
• Prior experience working in an autonomous or self-driving chemical lab environment driving organic chemistry transformations
• Hands-on experience with AI-driven experimental design or Bayesian optimization
• Background in scaling workflows from proof-of-concept to routine, high-throughput operation

Your Impact at LILA

The Scientist I/II, Organic Chemistry will develop, execute, and optimize modern chemical transformations that support Discovery Chemistry efforts across Lila’s platform, with a focus on the rapid synthesis of small molecules and structurally diverse chemical matter. This role is intended for an experimental organic chemist who combines strong foundations in synthetic chemistry with hands-on experience in high-throughput experimentation (HTE), reaction workup, and analytical characterization.

Working closely with Discovery Chemistry, analytical chemistry, automation, screening, and AI/computational teams, this scientist will help build and apply efficient chemistry workflows that accelerate molecular design–make–test–analyze cycles. The Scientist II will contribute to reaction development, analog generation, and route execution using modern organic chemistry approaches that are compatible with scalable, data-rich, and increasingly automated discovery environments.

This role is ideal for a chemist excited by solving synthetic problems at the interface of reaction innovation, high-throughput experimentation, process efficiency, and analytical insight, and who is motivated to help shape next-generation discovery workflows beyond traditional bench chemistry.

What You'll Be Building

• Design, execute, and optimize chemical transformations relevant to Discovery Chemistry programs, with emphasis on the rapid synthesis of small molecules and analog series.
• Apply modern synthetic organic chemistry to enable efficient exploration of structurally diverse and medicinally relevant chemical space.
• Plan and perform multi-step synthesis, reaction optimization, workup, purification, and compound characterization in support of molecular discovery campaigns.
• Design and execute HTE workflows for reaction screening, condition optimization, reagent evaluation, and rapid assessment of transformation scope.
• Develop robust approaches for reaction setup, reaction workup, sample preparation, and analytical readout to support fast and information-rich experimentation.
• Use analytical tools such as chromatography, NMR, and related methods to assess reaction performance, characterize products, and guide synthetic decisions.
• Contribute to the development of practical and scalable chemistry workflows that integrate reaction discovery, reaction optimization, and downstream compound generation.
• Partner closely with Discovery Chemistry scientists to translate molecular design concepts into executable synthetic strategies and experimentally tractable reaction plans.
• Collaborate with analytical chemistry and automation teams to build workflows that connect reaction execution with streamlined workup, purification, and data generation.
• Support the adaptation of synthetic workflows to parallel, automated, or robotics-enabled platforms where appropriate.
• Interpret reaction and analytical data rigorously, identify bottlenecks, and propose solutions to improve efficiency, robustness, and reproducibility.

What You’ll Need to Succeed

• PhD in Organic Chemistry, Medicinal Chemistry, or a closely related discipline with relevant postdoctoral and/or industry experience.
• Strong expertise in synthetic organic chemistry, including design and execution of multi-step synthesis and development of chemical transformations relevant to small molecule discovery.
• Hands-on experience with HTE for reaction screening, optimization, or scope evaluation.
• Experience with reaction workup, sample preparation, purification, and analytical characterization in fast-paced synthetic workflows.
• Strong working knowledge of analytical methods commonly used to support organic synthesis.
• Demonstrated ability to troubleshoot challenging reactions and independently solve synthetic and experimental problems.
• Strong understanding of how reaction design, execution, workup, and analysis fit together in efficient discovery workflows.
• Ability to work effectively in interdisciplinary environments spanning chemistry, analytics, automation, and computational sciences.
• Strong organizational, documentation, and communication skills, with commitment to scientific rigor and reproducibility.

Bonus Points For

• Experience supporting Discovery Chemistry or medicinal chemistry programs in biotech, pharma, or advanced research environments.
• Familiarity with modern reaction classes relevant to small molecule discovery, including coupling chemistry, heterocycle synthesis, late-stage functionalization, and rapid analog generation.
• Experience with parallel synthesis or robotics-enabled chemistry workflows.
• Exposure to data-rich, AI-enabled, or platform-based R&D environments.
• Collaborative mindset and enthusiasm for building modern chemistry capabilities that go beyond traditional bench-scale synthesis.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs
• Initial proof-of-concept safeguards, such as ML models to detect and block unsafe behavior from scientific AI models, as well as from physical lab outputs.
• Understanding of a range of model capabilities, across primarily scientific but also non-scientific domains (e.g. persuasion, deception) to inform Lila's broader safety strategy.
• Broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.

What You’ll Need to Succeed

• Bachelor's degree in a technical field (e.g., computer science, engineering, machine learning, mathematics, physics, statistics), or related experience.
• Strong programming skills in Python, and experience with ML frameworks (including, for instance, Inspect) for large-scale evaluation and scaffolded testing.
• Experience in building evaluations, or conducting red-teaming exercises, for CBRN / cyber risks (or for frontier model capabilities more generally, including both unsafe and benign capabilities)
• Experience in designing and/or implementing (directly or through consultation) AI safety frameworks for frontier AI companies.
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.

Bonus Points For

• Masters or PhD in a field relevant to safety evaluations of AI models in scientific domains, or a technical field.
• Publications in AI safety / evaluations / model behaviour in top ML / AI conferences (NeurIPS, ICML, ICLR, ACL) or model release system cards.
• Experience researching risks from novel science (e.g. biosecurity, computational biology, etc.) or working with narrow scientific tools (e.g. large scale foundation models for science).

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

Your Impact at LILA

The Senior Scientist, Analytical Chemistry will develop and deploy advanced analytical and characterization strategies to support Discovery Chemistry efforts across Lila’s platform, with a focus on enabling the rapid design, synthesis, screening, and optimization of small molecules and related molecular matter. This scientist will play a key role in generating high-quality, information-rich experimental data that informs chemistry decisions and accelerates platform learning.

Working closely with Discovery Chemistry, automation, AI/computational, and screening teams, this role will establish and scale multimodal characterization workflows that go beyond traditional analytical chemistry approaches. The Senior Scientist will help build an integrated analytical capability spanning compound characterization, reaction monitoring, molecular profiling, and high-throughput data generation to support fast and iterative design–make–test–analyze cycles.

This role will be critical to shaping Lila’s next-generation discovery engine by combining deep expertise in analytical chemistry with high-throughput experimentation, multimodal data generation, AI-enabled workflows.

What You'll Be Building

• Develop, optimize, and implement analytical and multimodal characterization workflows to support Discovery Chemistry programs and molecular discovery campaigns.
• Support the design, synthesis, screening, and optimization of small molecules by delivering rapid, reliable, and information-rich analytical data.
• Lead analytical method development for compound identification, purity assessment, impurity profiling, reaction monitoring, and molecular characterization using techniques such as liquid chromatography, mass spectroscopy, NMR, and complementary orthogonal methods.
• Build characterization strategies that extend beyond traditional analytical methods, incorporating multimodal measurements that provide deeper insight into molecular identity, reaction outcomes, physicochemical properties, and structure–function relationships.
• Partner closely with Discovery Chemistry and screening teams to support high-throughput screening and high-throughput experimentation workflows, including rapid sample analysis, reaction triage, and compound profiling.
• Collaborate with automation and platform teams to integrate analytical instrumentation and data pipelines into robotics-enabled and scalable discovery workflows.
• Work closely with AI and computational teams to ensure analytical datasets are structured, interoperable, and useful for model development, closed-loop learning, and iterative molecule design.
• Establish robust workflows for reaction monitoring, in-process analytics, final compound quality assessment, and characterization of complex mixtures or intermediates.
• Troubleshoot analytical and characterization challenges related to sample preparation, instrumentation, method robustness, data interpretation, and workflow integration.
• Contribute to the development of platform-level capabilities for data-rich molecular discovery, including scalable characterization pipelines, method standardization, and best practices for analytical rigor.

What You’ll Need to Succeed

• PhD in Analytical Chemistry, Organic Chemistry, Pharmaceutical Sciences, Chemical Biology, or a related scientific discipline with 5–8+ years of relevant industry or high-performance research experience.
• Deep expertise in analytical chemistry and molecular characterization in support of chemistry-driven discovery efforts.
• Strong hands-on experience with key analytical techniques for small molecule analysis.
• Demonstrated experience developing analytical methods for compound characterization, reaction monitoring, impurity analysis, and purity assessment.
• Experience supporting Discovery Chemistry, medicinal chemistry, synthetic chemistry, or other molecule-focused R&D environments.
• Strong understanding of how analytical data informs compound progression, screening decisions, reaction optimization, and molecular design.
• Experience working with or supporting high-throughput workflows, including rapid analytical turnaround in fast-paced research settings.
• Ability to solve complex analytical problems independently and work effectively across interdisciplinary teams spanning chemistry, screening, automation, and computational sciences.
• Strong documentation, communication, and data interpretation skills, with a commitment to rigor, reproducibility, and scientific quality.

Bonus Points For

• Experience with multimodal characterization approaches that combine orthogonal measurements to generate deeper insight into molecular systems and discovery workflows.
• Experience supporting high-throughput screening, reaction screening, or automated discovery platforms.
• Familiarity with analytical workflows integrated with robotics, liquid handlers, autosamplers, or other automation-enabled laboratory systems.
• Experience working in AI-enabled or highly data-driven R&D environments where experimental data is used to drive predictive modeling or closed-loop optimization.
• Knowledge of characterization approaches that extend beyond traditional compound QC, including molecular profiling, reaction analytics, and property-focused measurements.
• Familiarity with data systems such as ELNs, LIMS, and software tools used to manage and analyze large analytical datasets.
• Ability to operate effectively in a fast-moving, innovative environment with evolving platform needs and cross-functional priorities.
• Strong scientific curiosity and interest in building next-generation analytical capabilities for molecular discovery.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Set the build and research strategy for Lila’s safety approach to biological / physical risks.
• Design and build capability evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs, across biological / physical sciences.
• Coordinate and lead threat modelling exercises with internal and external scientific experts, including monitoring for emerging technologies and use-cases.
• Develop and curate high-quality training and test data for evals and safety systems.
• Evaluate risks from Lila’s capabilities, including through interactions with the wider ecosystem of capabilities (e.g. general-purpose frontier models as well as narrow scientific tools)
• Contributing to broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.
• Contribute to external communications on Lila’s safety efforts.

What You’ll Need to Succeed

• A PhD in either a biological sciences domain (e.g., molecular biology, virology, computational biology or related fields) or a physical sciences domain (materials sciences, physics, chemistry, chemical or nuclear engineering, or related fields), or other related experience.
• Demonstrated ability to set research directions for open problems in dual-use risks in the biological / physical sciences.
• Experience in scientific computing, across either biological or physical sciences.
• Familiarity with dual-use research and dissemination concerns, across the relevant safety / regulatory / governance frameworks (e.g. export control frameworks, biological and chemical-related conventions and controls).
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.
• Demonstrated ability to lead teams of internal and external collaborators in buildout of Lila’s point-of-view on biological / physical risks
• Demonstrated ability to deal with cross-functional stakeholders (science, AI, product, policy) in a complex environment.

Bonus Points For

• Experience in developing or applying ML to biological or physical sciences
• Experience in building evaluations, or conducting red-teaming exercises, across scientific risks for frontier models / narrow scientific tools.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

Your Impact at LILA

We are seeking a motivated and detail-oriented Senior Research Associate / Associate Scientist to join our high-throughput autonomous chemistry team. This is a hands-on role at the intersection of organic and inorganic synthesis, advanced characterization, and laboratory automation. You will design and execute high-throughput experiments, synthesize small molecules, and perform rigorous downstream analysis while working side-by-side with senior scientists to translate ambitious product goals into scalable experimental workflows that directly drive our company’s growth.

This position offers first-hand exposure to automated chemistry platforms, with real ownership over experiments that inform company strategy and scientific direction. Ideal candidates are execution-driven, thrive in fast-paced laboratory environments, and are eager to build deep technical expertise while contributing meaningfully to next-generation chemical discovery at Lila Sciences.

What You'll Be Building

• Independently execute experiments to synthesize, purify, and characterize organic and inorganic small molecules
• Optimize reactions, perform method development, and interpret analytical data to guide project decisions
• Translate early-stage ideas into reproducible, functional experiments
• Apply retrosynthetic planning to support target molecule synthesis
• Operate Schlenk lines, gloveboxes, and other inert-atmosphere systems for sensitive compounds
• Use PAT tools (UPLC, LCMS, NMR, IR, Fluroescence, DLS) to monitor reactions, ensure quality control, and generate high-quality data for ML workflows
• Leverage automation and AI-driven platforms to accelerate workflows and reduce experimental cycle times
• Collaborate with engineers, ML scientists, and stakeholders to validate model-suggested conditions, analyze trends, troubleshoot issues, and communicate results clearly through reports, discussions, and presentations
• Document results, maintain accurate digital records and adhere to EHS and laboratory best practices

What You’ll Need to Succeed

• M.S. in Chemistry or related discipline (organic, organometallics, catalysis) with 2+ years of hands-on high-fidelity laboratory experience in an academic or industry setting, or B.S. + 5 years
• Hands-on experience in organic/inorganic synthesis, purification, chromatographic techniques, product analysis
• Strong understanding of retrosynthesis, reaction mechanisms, and method optimization workflows
• Proficiency with analytical techniques such as TLC, HPLC, LCMS, NMR, and IR
• Ability to follow SOPs and work safely with diverse chemical reagents and automated platforms
• Ability to thrive in a fast-paced, multidisciplinary research environment
• Required proficiency in using SciFinder, Reaxys, Chemdraw to search public database and literature
• Basic proficiency in Python or other scripting languages for data handling
• Good document practices, strong attention to detail and a proactive, problem-solving mindset
• Effective oral and written communication skills; contributed to internal reports, technical documentation, or peer-reviewed publications

Bonus Points For

• Experience with high-throughput or AI-driven automated platforms
• Authored publications in peer-reviewed journals in chemical catalysis, organic methodology
• Ability to handle air/moisture/light sensitive compounds

Your Impact at LILA

Lila Sciences is seeking an experienced Senior Research Associate to join our Antibody Platform team. In this role, you will play a pivotal role in building Lila's Scientific Superintelligence platform by leveraging your deep expertise in high-throughput antibody discovery, production, and characterization.

What You'll Be Building

• Design, optimize and execute high-throughput workflows for antibody expression and purification. Drive platform evolution by identifying opportunities to improve efficiency, robustness, and scalability of antibody production.
• Collaborate closely with scientists, engineers, and automation experts to discover, evaluate and implement novel automation tools, technologies, and reagents to expand the Antibody Platform’s capabilities.
• Innovate and adapt protocols to accommodate new antibody formats, targets, and expression strategies.
• Analyze antibody yield and binding characteristics using biolayer interferometry (BLI) and other relevant techniques; interpret and communicate findings effectively.
• Ensure data quality, documentation, and reproducibility in all experiments; actively contribute to knowledge sharing and continuous improvement initiatives. Collaboration, flexibility, and creative problem-solving are key to thrive in this dynamic role.

What You’ll Need to Succeed

• Bachelor’s or Master’s degree in Biochemistry, Molecular Biology, Bioengineering, or related discipline with 2–5+ years of hands-on industry or academic experience.
• Proficiency with antibody expression in CHO-S, including DNA transfection, small-scale cell culture, and antibody characterization; ExpiCHO expertise strongly preferred.
• Experience using sequence analysis software for molecular biology workflows and annotating antibody sequences, specifically Geneious, Benchling, PipeBio, etc.
• Experience with liquid handling automation and high-throughput formats.
• Experience with biolayer interferometry (BLI) or surface plasmon resonance (SPR) quantitative binding assays, CE-SDS, and antibody developability assays.
• Outstanding troubleshooting skills, adaptability, and ability to drive innovation in experimental design.
• Familiarity with laboratory data analysis, digital recordkeeping, and collaborative scientific workflows.
• Strong communication skills and an eagerness to collaborate with a fast-paced, cross-functional team.

Bonus Points For

• Skilled in cloning, expression and optimization of multispecific antibody formats
• Data analysis using relevant software (Python, R, Spotfire, or similar)
• Scripting for automation platforms

Your Impact at LILA

We are seeking a (Senior) Research Associate to join our Life Sciences team. This role will focus on formulating lipid nanoparticles (LNPs), functionalizing them with targeting ligands, and characterizing the resulting targeted LNPs (tLNPs). The ideal candidate will have hands-on expertise in LNP formulation and characterization, bioconjugation, protein characterization, and automation technologies. Your work will unlock new understandings in the delivery space by enabling a high-throughput closed-loop screening cascade for tLNPs. This position will work closely with others across the protein, cell biology, automation, chemistry machine learning, and data science teams to help establish high-throughput next-generation tools for targeted nucleic acid delivery.

What You'll Be Building

• Design, execute, and characterize (DLS, ribogreen, TNS, etc.) LNP formulations across multiple scales and mixing modalities
• Develop and refine high-throughput ligand conjugation and purification methods, employing automation and robotics to increase throughput
• Collaborate with cell assay and antibody specialists to screen hits across a variety of tissue targets in in vivo models
• Collaborate with chemists, biologists, engineers, and data scientists to document systems, share insights, and refine best practices in autonomous flow chemistry
• Write, implement, and maintain Standard Operating Procedures (SOPs) for both existing and new lab processes

What You’ll Need to Succeed

• MSc in Chemical Engineering, Biomedical Engineering, Pharmaceutical Sciences, or a related field with 3+ years, or BSc with 5+ years, of hands-on experience in targeted LNP production, or related experience. Industry experience strongly preferred
• Strong working knowledge of bioanalytical techniques (e.g., DLS, fluorescence spectroscopy, electrophoresis, in vitro assays)
• Experience with protein and antibody design and characterization
• Familiarity with automation and high-throughput workflows
• Excellent troubleshooting, communication and collaboration skills, with a proven ability to work effectively across interdisciplinary teams

Your Impact at LILA

We are seeking a motivated and detail-oriented Associate Engineer to join our high-throughput Research Operations team. In this role, you will focus on materials characterization of materials using spectroscopy and microscopy techniques

You will gain hands-on experience with state-of-the-art automation technologies while contributing directly to projects that drive our company’s growth.

This is an excellent opportunity for candidates excited to learn engineering principles, work with advanced laboratory automation, and develop a strong foundation in scientific operations in a dynamic environment.

What You'll Be Building

• Perform materials characterization techniques including SEMXRF, XRD, Optical Microscopy, Nanoindentation, and Profilometer
• Prepare reagents, solutions/electrolytes , samples, and consumables to ensure seamless continuation of experiments across shifts
• Follow detailed standard operating procedures (SOPs) to ensure accuracy, reproducibility, and throughput
• Monitor workflow performance, troubleshoot common issues, and escalate when necessary to ensure continuity between shifts
• Record, organize, and maintain experimental data with high attention to detail
• Identify opportunities to improve efficiency and streamline processes across shift operations
• Flag unusual features or results for scientist review
• Collaborate with scientists and engineers to support diverse projects across life sciences and physical sciences

What You’ll Need to Succeed

• Bachelor’s degree in Chemistry, Physics, Chemical/Materials Engineering, or a related field (or equivalent laboratory experience)
• Attention to detail and strong organizational skills
• Basic understanding of electron microscopy principles
• Hands-on SEM experience (academic or industry). EDS experience is nice to have.
• Experience with sample preparation techniques: sputter coating

Bonus Points For

• Familiarity with surface characterization techniques methods: XRF, optical microscope, XRF, XRD, nanoindentor, profilometer.
• Experience working in high-throughput production environments with a focus on scalability, efficiency, and accuracy
• Basic engineering skills for troubleshooting characterization tools for microscopes, x rays, and lasers
• Familiarity with automated workflows and techniques to operate and generate custom scripts

Your Impact at LILA

As a ML Research Scientist - Multimodal Data Extraction, you will advance Lila’s vision of scientific superintelligence by developing foundation models that autonomously read, interpret, and structure scientific knowledge across text, images, and experimental data in the physical sciences. Your research will help unify the world’s scientific information into machine-understandable form, powering reasoning, prediction, and autonomous discovery across materials science and chemistry.

What You'll Be Building

• Research and develop AI systems that extract and structure knowledge from diverse scientific sources.
• Design and fine-tune large language, multi-modal and specialized models for factual, interpretable data extraction.
• Build scalable pipelines for unstructured and heterogeneous scientific data, integrating text, tables, and visuals.
• Collaborate with domain experts to align extracted data with real-world discovery workflows.
• Publish research that advances the state of the art in multimodal understanding and AI-driven knowledge extraction.

What You’ll Need to Succeed

• PhD (or equivalent research experience) in Computer Science, Chemistry, Materials Science, or related field.
• Expertise in machine learning, NLP, and vision–language modeling using PyTorch and Hugging Face Transformers.
• Proven ability to train, fine-tune, and evaluate LLMs and multimodal models for scientific data extraction.
• Strong understanding of data structures and representations used in the physical sciences.
• Demonstrated research impact through publications, preprints, or open-source work (e.g., NeurIPS, ICLR, ICML, ACL, EMNLP, Scientific Journals).

Bonus Points For

• Experience with multimodal fusion architectures and document-level understanding.
• Knowledge of scientific document parsing (OCR, table extraction, figure-caption linking).
• Familiarity with knowledge graph construction or reasoning systems for science.
• Experience with noisy or heterogeneous real-world scientific data.
• Collaborative mindset and passion for advancing AI in the physical sciences.

Your Impact at LILA

Your role in our Physical Sciences division will focus on designing and implementing state-of-the-art simulation approaches to model transport, kinetics, rare events, and reaction networks, and integrating them with AI-driven platforms for materials discovery. Your work will be integral to our efforts in predicting, designing, and controlling the behavior of complex materials and molecular systems, and their acceleration via agentic AI. You will partner with diverse teams at Lila, including machine learning experts working on scientific superintelligence and materials science experts performing real-world experiments.

What You'll Be Building

• Develop and extend molecular dynamics and Monte Carlo algorithms to capture rare events, non-equilibrium processes, transport phenomena, and mapping complex reaction networks.
• Build scalable simulation workflows that integrate statistical mechanics methods with machine learned interatomic potentials and agentic AI frameworks.
• Design methods for coupling dynamics simulations with experimental observables to enable closed-loop verification and discovery with automated labs.
• Collaborate with computational scientists, machine learning experts, and platform engineers to advance the fidelity and scalability of simulation-driven materials discovery.
• Establish reproducible, modular software pipelines for statistical mechanics and dynamics simulations that can be deployed on HPC and cloud-based infrastructure.

What You’ll Need to Succeed

• PhD or equivalent research/industry experience in Physics, Chemistry, Chemical Engineering, Mechanical Engineering, Applied Mathematics, or related fields.
• Strong background in statistical mechanics, free energy calculations, reaction mapping, non-equilibrium dynamics, and rare-event sampling.
• Demonstrated expertise with molecular dynamics, Monte Carlo, and/or kinetic simulation software and frameworks (LAMMPS, GROMACS, OpenMM, HOOMD, etc.).
• Solid programming skills and experience with scientific computing (Python, C/C++, MPI, CUDA, etc.).
• Experience running and automating simulations on HPC and/or cloud environments at scale.

Bonus Points For

• Strong publication record applying advanced statistical mechanics or dynamics simulations to molecular and materials systems, including but not limited to molecular/biomolecular systems and solid-state materials and interfaces.
• Prior work in coupling dynamics simulations with data-driven, AI-based, and/or agentic frameworks.
• Good familiarity with machine learning frameworks (PyTorch, JAX, TensorFlow, etc.)
• Prior experience working with machine learned interatomic potentials, including model training, fine-tuning, and data generation
• Worked closely with experimental teams to extract and corroborate experimental observables from dynamics simulations

Your Impact at LILA

As a member of our team in the Physical Sciences division, you will design and build intelligent agent-driven systems that enable AI-accelerated and AI-orchestrated process engineering across a broad range of industrial applications. The core mission of this role is to develop methods by which AI agents can reason about, design, simulate, optimize, and operate complex physical and chemical processes using existing or ML-driven process engineering tools. You will focus on creating agentic infrastructures that allow AI systems to plan and execute multi-step process engineering workflows, ranging from process synthesis and flowsheet generation to steady-state and dynamic simulation, control strategy design, and techno-economic evaluation. Your work will directly shape how Lila’s scientific superintelligence performs closed-loop autonomous process engineering to solve real-world problems.

What You'll Be Building

• Architect and implement agentic frameworks that support end-to-end process engineering workflows, including process setup, simulation, optimization, and analysis.
• Develop AI agents capable of autonomously planning, executing, and iterating on process engineering tasks using existing tools (e.g., steady-state and dynamic simulators, optimizers, and data systems).
• Explore agentic approaches for advanced tasks such as process intensification, control co-design, real-time optimization, and closed-loop learning from operational data.
• Improve robustness, interpretability, and reproducibility of agent-driven process engineering workflows; build internal tooling for debugging, observability, validation, and auditability.
• Work with interdisciplinary teams to apply agentic process engineering to a broad range of industrial applications

What You’ll Need to Succeed

• PhD or equivalent experience in Chemical Engineering, Industrial Engineering, Systems Engineering, or a closely related field.
• Research experience in method development for process engineering, a strong publication record in this area or established industry experience
• Hands-on experience with process simulation and optimization tools (commercial or open-source), including steady-state and dynamic modeling.
• Proficiency in Python and scientific/engineering computing ecosystems
• Experience integrating external engineering tools or simulators into automated workflows via APIs, scripting interfaces, or custom wrappers.
• Familiarity with distributed systems, HPC environments, cloud platforms, or scalable compute infrastructure.

Bonus Points For

• Experience developing or integrating agentic frameworks, autonomous planners, or multi-step tool-using AI systems for engineering or scientific domains.
• Experience building computational pipelines, automation systems, or tool-use frameworks for complex engineering or scientific workflows.
• Experience with digital twins, real-time optimization, or model-predictive control frameworks.
• Background in techno-economic analysis (TEA), life-cycle assessment (LCA), or sustainability-driven process design.
• Contributions to open-source engineering software, ML infrastructure, workflow engines, or agent frameworks.

About the Role

Accelerating clinical research is one of the defining challenges in healthcare. Promising therapies exist that patients can't access because the operational infrastructure to run clinical trials efficiently doesn't exist yet. We're building it. That means designing technology systems that bring order to a fragmented landscape of clinical data sources, automating the operational work that slows trials down, and turning real-world clinical data into a foundation for predictive intelligence.

We're looking for a Staff Data Scientist to be the person who understands our data deeply enough to know what's possible and curious enough to prove it. We have a truly unique data set within the industry, connecting clinical data (emr, endoscopic video, etc…) to trial data across 80+ trial sites. We're looking for someone who wants to dig deeply into this data - to understand its structure, its gaps, what it can tell us - and connect that understanding to real outcomes for sites and patients. The landscape is evolving rapidly, and the right person will have a point of view on how to apply new capabilities to our specific data and problems as they emerge.You'll work hands-on with the data, structure experiments, evaluate what's modelable, and directly influence what we build and how. This role sits at the intersection of data science, product strategy, and ML: you'll lay the foundation for our predictive capabilities and shape what that function becomes.

This is an opportunity for someone who wants to be part of a small, fast-moving engineering team at a formative stage. You'll shape what gets built, how decisions get made, and what the team becomes.

Responsibilities

• Work with clinical, video, and clinical trial operational data to understand what's there, what's meaningful, and how we can use it to drive a more efficient clinical trial system
• Design and run experiments that determine what's worth building
• Stay close to the evolving ML and model landscape and bring a point of view on how new capabilities apply to our data and problems
• Define the path from raw data to product and operationalization: what to model, how to evaluate it, and when it's ready to ship
• Partner with product and engineering to translate findings into concrete product decisions
• Identify opportunities where our data creates unique predictive advantages
• Evaluate where we should build, where we should partner, and where existing approaches fall short
• Help shape the engineering culture of a small, growing team: how technical decisions get made, how problems get debated, what rigor looks like in practice

What We’re Looking For

Required Qualifications

• 5+ years of experience in data science, applied ML, or quantitative research, with significant time spent hands-on with data
• Experience with healthcare data, clinical research, or life sciences
• A deep curiosity to understand data and connect it to the real world
• Deep experience designing and running experiments: you know how to structure a question, test it honestly, and draw conclusions that hold up
• Strong statistical foundations and the judgment to know when a result is meaningful versus interesting
• Fluent in Python and SQL, comfortable working across the data stack from exploratory analysis through to production-ready pipelines
• Experience working across data science, product, and engineering: you can influence what gets built, not just analyze what exists
• Have worked with complex, messy, real-world data and know how to make it useful without pretending it's clean
• Knowledgeable about ML capabilities and frameworks, with the judgment to know when something is genuinely applicable versus hype
• Can communicate findings clearly to technical and non-technical audiences, and make a persuasive case for what to build next

Preferred Qualifications

• Experience working at growth stage startups (strongly preferred)
• Experience with medical imaging or video data
• Familiarity with clinical trial operations, disease classification, or patient identification problems
• Experience building or defining the roadmap for an ML function from early stages
  • A track record of data science work that directly changed product direction

Company description

Serif Biomedicine is a privately held, early-stage biotechnology company developing a novel approach to gene therapy that can address currently untreatable diseases. It was founded by Flagship Pioneering, an innovation enterprise that conceives, creates, resources, and grows first-in-category life sciences companies.

Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA), Syros Pharmaceuticals (SYRS), Seres Therapeutics (NASDAQ:MCRB), Generate Biomedicines, Tessera Tx, Evelo Biosciences (EVLO), and Indigo Agriculture.

The role

We are seeking a highly experienced Lipid Nanoparticle (LNP) Formulation Senior Scientist to lead the design, execution, and interpretation of advanced Design of Experiments (DOE) strategies to drive innovation in next-generation LNP formulations. This role will play a central role in shaping formulation and delivery strategies for nucleic acid therapeutics within a dynamic and collaborative research environment.

The successful candidate will not only develop, optimize, and characterize LNP systems, but also lead the design and establishment of a high-throughput LNP screening platform spanning in vitro systems and small and large animal models. This includes defining experimental frameworks, selecting and implementing appropriate assays, and building scalable workflows to accelerate candidate evaluation and selection.

As a senior scientific contributor, this individual will be expected to operate with a high degree of independence, influence cross-functional program direction, and identify innovative solutions to advance platform capabilities. The role also includes mentoring junior scientists and contributing to the broader scientific strategy through internal leadership and external scientific engagement.

Key responsibilities

• Drive the development, optimization, and implementation of a high-throughput LNP screening platform across small and large animal models, including experimental design, assay selection, and data analysis pipelines.
• Independently define scientific strategies and experimental roadmaps aligned with program goals.
• Serve as a scientific lead for one or more programs, influencing cross-functional decisions across biology, formulation, and translational teams.
• Identify technical gaps and proactively propose innovative solutions to improve platform capabilities and throughput.
• Mentor junior scientists and contribute to building a strong, collaborative scientific culture.
• Communicate findings clearly to internal stakeholders and external partners; contribute to publications, patents, and regulatory documentation.
• Stay at the forefront of LNP delivery technologies and emerging screening methodologies, integrating new approaches where appropriate.

Professional experience and qualifications

• PhD or MS in Chemistry, Pharmaceutical Sciences, Chemical Engineering, Materials Science, or a related field and 5+ years of industry experience 
• Proven track record of independently leading research projects and delivering impactful results.
• Demonstrated experience in nanoparticle/LNP design, screening, and in vivo evaluation, preferably including large animal models.
• Experience in developing or scaling high-throughput screening platforms is strongly preferred.
• Strong understanding of experimental design, statistics, and data interpretation.
• Evidence of scientific leadership (e.g., mentoring, leading collaborations, publications, patents).
• Excellent communication and cross-functional collaboration skills.
• Strong hands-on experience with LNP formulations, including formulation development and optimization

What We Offer

• Opportunity to work at the forefront of LNP formulation innovation
• Collaborative, science-driven culture with high impact research
• Competitive compensation and benefits package

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 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 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 annual list of the World Most Innovative Companies. Learn more about Flagship https://url.us.m.mimecastprotect.com/s/xLXBCqxk3LTk9pwcZf3CEkjif?domain=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.

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 - $181,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL87 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL87's good faith estimate as of the date of publication and may be modified in the future.

Company Description: 

In today’s healthcare system, disease diagnosis often relies on invasive procedures, such as biopsies, which enable direct interrogation of cellular and tissue health at the suspected source of disease. Due to their invasiveness, cost, and general inconvenience to the patient, biopsies are often conducted after onset of symptomatic disease presenting one of the largest barriers to delivering interventions early in disease progression when they are likely to be most impactful. Flagship Labs 103, Inc. is a privately held early-stage company that is building advanced technological and computational platforms to pioneer the detection of cellular dynamics from minimally invasive biospecimens that can be leveraged to connect individuals to the most effective interventions to prevent onset and progression of disease

Job Description:

We are seeking an experienced and motivated Senior Scientist to join and lead our conjugation efforts to drive FL103’s programs forward. Ideal candidates will be self-motivated, independent, and committed to the generation of high-quality data within a fast-paced and innovative research team. The Conjugation Biochemist will support ongoing bioconjugation projects in several research and development areas.

Essential Responsibilities:

• Design, synthesis, purification and analysis of oligonucleotide-conjugates on antibodies and other modalities. Develop and optimize conjugation protocols using established and novel chemistries and technologies as part of an assay development platform.
• Collaborate closely with the assay development team to guide and optimize conjugates to support FL103’s programs.
• Work as part of a cross-functional team to manage and maintain progress against multiple project timelines, deliver routine updates, and communicate progress to the team.
• Establish and maintain excellent working relationships with critical collaborative partners throughout the company to advance discovery research activities to pre-clinical development.
• Contribute to the preparation of research reports and presentations for internal project teams, leadership team, and external audiences.
• Maintain updated and well-organized lab notebooks and batch records.

Required Qualifications:

• Ph.D. in Biochemistry, Chemistry, or related scientific discipline
• 5+ years of bioconjugation-related industrial experience, preferably in designing, preparing, and validating oligonucleotide conjugates.
• Understanding project timelines and deliverables and plans/coordinate project work accordingly with departmental, functional, and external stakeholders.
• Strong problem-solving skills and a proactive attitude towards exploring new approaches.
• Demonstrates strong written and verbal communication skills, with the ability to clearly present complex scientific data to cross‑functional and senior leadership teams.
• Hands-on expertise with current and cutting-edge bioconjugation techniques for antibodies, proteins, peptides, and other biomolecules.
• Demonstrated hands‑on experience in analytical characterization of conjugates with a strong analytical mindset.  Proficiency in purification techniques such as RP-HPLC, FPLC, SEC, and IEX.
• Able to work independently or in cross-functional team settings with minimal supervision.
• Adaptable and flexible, able to navigate shifting priorities and handle day‑to‑day challenges with professionalism and confidence in fast‑moving environments.
• Self‑motivated with strong interpersonal, organizational, and communication skills, and able to take a hands‑on approach in a dynamic, fast‑paced, and collaborative environment.

About Flagship Pioneering

Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com

Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.

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 - $181,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL103 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL103's good faith estimate as of the date of publication and may be modified in the future.

Company description

Serif Biomedicines is a privately held, early-stage biotechnology company developing a novel approach to gene therapy that can address currently untreatable diseases. It was founded by Flagship Pioneering, an innovation enterprise that conceives, creates, resources, and grows first-in-category life sciences companies.

Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA), Syros Pharmaceuticals (SYRS), Seres Therapeutics (NASDAQ:MCRB), Generate Biomedicines, Tessera Tx, Evelo Biosciences (EVLO), and Indigo Agriculture.

The role

We are seeking a motivated Associate Scientist to support the development, preparation, and characterization of Lipid Nanoparticle (LNP) formulations. This role is highly hands-on and focused on formulating, screening, and analyzing LNPs to support discovery and development programs. The ideal candidate works well in a fast-paced, team-oriented environment and is eager to deepen their expertise in formulation science.

Key responsibilities

• Prepare and formulate LNPs using established protocols and evolving methods
• Execute formulation experiments to support optimization and screening efforts
• Perform LNP characterization and analytics, including particle size, PDI, encapsulation efficiency, and stability testing
• Accurately document experimental procedures, results, and observations in laboratory records
• Analyze and summarize experimental data and communicate findings to project teams
• Collaborate closely with scientists across formulation, analytics, and biology functions
• Support routine laboratory operations, including reagent preparation, equipment upkeep, and inventory management

Professional experience and qualifications

• BS or MS in Chemistry, Biochemistry, Pharmaceutical Sciences, Chemical Engineering, or a related field and 8+ years of industry experience
• Hands-on experience with LNP formulations or lipid-based delivery systems
• Familiarity with LNP analytical techniques (e.g., DLS, encapsulation assays, basic stability studies)
• Strong attention to detail and ability to follow experimental protocols
• Ability to work effectively as part of a team in a fast-paced environment
• Good written and verbal communication skills

What We Offer

• Opportunity to work at the forefront of LNP formulation innovation
• Collaborative, science-driven culture with high impact research
• Competitive compensation and benefits package

LOCATION: Cambridge, MA

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 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 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 annual list of the World Most Innovative Companies. Learn more about Flagship https://url.us.m.mimecastprotect.com/s/xLXBCqxk3LTk9pwcZf3CEkjif?domain=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.

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 $96,000 - $126,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Serif Biomedicines currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Serif Biomedicine'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 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.

Position Summary

We are seeking a Scientist to join a dynamic team applying computational and data-driven approaches to design novel antigens and evaluate vaccine responses. At Apriori Bio, we have built our biology-enabled AI/ML platform Octavia™ to map viral fitness landscapes, predict immune escape trajectories, and design vaccines to elicit an optimal protective response to future challenges. The successful candidate will contribute to the development and application of computational methods—including structural modeling, machine learning, and statistical inference— that build on Octavia™ insights to support the company’s vaccine design efforts. Experience working with protein engineering and immunological datasets is valuable, as is interest or training in high-throughput functional genomics, virology, or vaccinology.

The Scientist will work closely with both computational and experimental colleagues to interpret results, generate hypotheses, and support antigen design. This role is ideal for scientists eager for a unique opportunity to learn and innovate within an interdisciplinary, fast-paced startup environment.

Key Responsibilities

• Use high-dimensional datasets (e.g., mutational scanning, NGS-based phenotypic screens) and computational approaches—including structural modeling, sequence analysis, and machine learning—to support antigen and immunogen engineering
• Apply and refine computational models that integrate screening data with structural and sequence-based features to guide biomolecule engineering
• Generate hypotheses and design analyses that inform evaluation of novel immunization strategies (in partnership with experimental teams)
• Identify, evaluate, and curate external datasets relevant to vaccine design and antigen optimization
• Develop reproducible computational tools and pipelines for data-driven product design that can be integrated into broader platform workflows
• Collaborate with engineers, computational scientists, and experimentalists to execute project goals and ensure smooth integration of computational findings
• Work with immunology and characterization teams to interpret vaccine immunogenicity using next-generation immune monitoring and antibody profiling tools
• Clearly communicate results and insights to colleagues across scientific and cross-functional teams
• Tackle difficult scientific problems with creativity and resilience while iterating quickly as new data emerges
• Take ownership of complex, open-ended scientific questions, driving analyses forward through ambiguity while balancing speed, rigor, and collaborative problem-solving

Basic Qualifications

• Ph.D. in bioengineering, immunology, computational biology, or a related field (or equivalent research experience)
• Experience applying data-driven protein engineering methods to predict and affect protein function, including structural and sequence-based machine-learning approaches
• Experience or training in antigen design leveraging vaccine immune response readouts
• Solid statistical and quantitative foundation, with the ability to translate complex biological datasets into actionable insights
• Strong scientific programming skills (Python preferred) and familiarity with best practices in reproducible scientific computing
• Experience working with high-throughput biological data or NGS-based assays, including modeling and statistical analysis
• Experience using version control and collaborative coding workflows

Preferred Qualifications

• Experience in vaccine design
• Experience with deep learning approaches
• Exposure to antibody characterization, immune profiling, or immune repertoire analyses
• Experience with NGS data pipelines, from processing to interpretation
• Familiarity with cloud or distributed computing environments
• Familiarity with storage, analysis and transformation of large tabular datasets and relational databases
• Laboratory experience in molecular biology, biochemistry, or immunology (a plus, not required)

About Flagship

Flagship Pioneering is a biotechnology company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com. 

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.

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 $115,000 - $165,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Apriori Bio, Inc. currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Apriori Bio, Inc.'s good faith estimate as of the date of publication and may be modified in the future.

What if… you could pioneer a new approach to designing life’s most essential molecules?

FL116, backed by Flagship Pioneering, is an early-stage biotechnology company transforming the way biomolecules are synthesized. Our innovative platform has the potential to transform how critical research, diagnostic, and therapeutic molecules are manufactured. We are seeking passionate problem solvers ready to make a profound impact on biotechnology and therapeutic innovation.

Position Summary

We are seeking a motivated, detail-oriented, and intellectually curious Research Associate or Senior Research Associate to join our Chemical Biology team. This role is centered on applying chemistry to solve complex biological problems, interrogating and controlling enzyme-driven biomolecular synthesis through a mechanistic and molecular lens.

You will execute high-throughput experiments to probe enzyme–substrate interactions, characterize biomolecule products, and contribute to the development of robust, scalable assays that power our platform. The ideal candidate appreciates the dynamic chemical nature of biological systems and is excited to manipulate and measure biology at the molecular level.

This is an exciting opportunity to build deep expertise at the interface of chemistry and biology within a fast-paced, collaborative startup environment. You are a hands-on experimentalist who thrives in execution-focused, pipeline-driven work and is eager to grow alongside a rapidly evolving technology platform.

Key Responsibilities

• Execute high-throughput experiments to characterize enzyme–substrate and enzyme–product interactions, with a focus on understanding underlying chemical mechanisms
• Apply chemical principles to modulate and interrogate protein function, reactivity, and biomolecular synthesis pathways
• Perform biomolecular product characterization using analytical and separation techniques (e.g., gel electrophoresis, TapeStation, HPLC, plate-based assays)
• Support the development, optimization, and scaling of biochemical and enzymatic assays with an emphasis on quantitative, reproducible readouts
• Generate, analyze, and interpret experimental datasets to extract mechanistic insight and inform pipeline progression
• Collaborate closely with cross-functional teams, including Enzyme Science and Assay Development, to integrate chemical insight into broader platform workflows
• Maintain rigorous experimental documentation and contribute to protocol development and knowledge sharing across the team

Qualifications

• B.S. or M.S. in Chemistry, Chemical Biology, Biochemistry, Biotechnology, or a related discipline with a strong foundation in chemical principles applied to biological systems
• 2+ years of relevant laboratory experience (industry or academic)
• Hands-on experience applying chemistry to biological systems, including enzymatic assays, biomolecule manipulation, or reaction-based workflows
• Strong foundation in protein chemistry, enzymology, or biomolecular interactions
• Proficiency in core laboratory techniques including pipetting, gel electrophoresis, and quantitative assay execution
• Demonstrated ability to generate high-quality, reproducible data and perform rigorous data analysis
• Experience working in fast-paced, collaborative laboratory environments

Preferred Qualifications

• Experience with analytical and separation techniques such as HPLC, capillary electrophoresis, TLC, or plate-based detection systems
• Exposure to bioorthogonal chemistry, chemical modification of biomolecules, or mechanistic enzymology
• Familiarity with nucleic acid or protein characterization platforms (e.g., TapeStation or similar technologies)
• Experience contributing to assay development, optimization, or high-throughput workflows
• Experience preparing samples for NMR
• Familiarity with automation platforms for high throughput screening

Who You Are

Innovative Pioneer: You are excited by the opportunity to explore new scientific frontiers and apply chemical thinking to unlock biological complexity.

Collaborative Contributor: You work effectively across teams, communicate clearly, and value shared success in a highly interdisciplinary environment.

Inventive Problem Solver: You approach challenges with curiosity and creativity, using first-principles thinking to develop elegant experimental solutions.

Mission-Driven Individual: You are motivated by the opportunity to fundamentally change how biomolecules are synthesized and to impact human health and biotechnology.

Motivated Learner & Emerging Professional: You are eager to deepen your expertise in chemical biology, take ownership of your work, and grow into a highly capable scientist within a startup environment.

Values and Behaviors:

Flagship is an experiment in institutional, entrepreneurial, and innovation practiced in the context of a small company with an insurgent mindset. We are seeking individuals with an entrepreneurial spirit, strong communication skills, and comfort in working in and contributing to a dynamic and cross-functional team environment.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, we encourage you to apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background. The level of the role will be commensurate with the education and years of experience of the identified candidates.

Flagship Pioneering and our ecosystem companies are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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 $81,000 - $107,250. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL116 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL116's good faith estimate as of the date of publication and may be modified in the future.

Company Summary:

We are building a new venture, FL122, pioneering genomic technologies at the intersection of human health and assisted reproduction. The company was founded by Flagship Pioneering, an innovative enterprise that conceives, creates, resources, and grows first-in-category life sciences companies. Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA), Generate Biomedicines, Tessera Therapeutics, and Quotient Therapeutics. We are an equal opportunity employer.

Position Summary:

We are seeking a first Computational Genomics hire, who will conduct crucial research that will form the basis of the company’s scientific platform. As an early stage hire, you will operate with significant ownership, shaping analytical strategy from first principals, intersecting the fields of genomics, statistical genetics and statistical modeling. The role includes responsibility of the end-to-end delivery of computational research projects, including project design, implementation, interpretation and reporting results to senior leadership. We are looking for someone who is resourceful, is open to a rapidly changing, agile environment and has bias to action. The ideal candidate combines deep technical rigor with a growth mindset, pays attention to detail, and has a deep-rooted desire to achieve excellence. Being collaborative is key – the environment is an early stage startup, where all members of the team need to work closely together to break new ground in science.

Key Responsibilities:

• Deliver computational research projects with a high degree of autonomy, including project design, implementation, interpretation and reporting results to senior leadership
• Collaborate with cloud engineers to set up the required infrastructure to process and store genomics datasets
• Integrate multiple NGS data types into coherent analyses, going from raw input files to variant calls and higher level analyses
• Develop probabilistic and Bayesian models that rigorously incorporate priors, uncertainty, and missing data to inform decision-making
• Interact with external advisors, leveraging their inputs and building high-quality relationships

Requirements:

• Ph.D. in biology, statistics, genetics, computational biology or a related quantitative discipline with 5+ years of relevant post-academic or industry experience with an excellent research track record
• Deep expertise in the analysis of genomics data derived from Illumina sequencing platforms (expertise with additional sequencing technologies is a plus)
• Experience processing next-generation sequencing data end-to-end, from raw reads through alignment, QC, and variant calling
• Experience integrating and jointly analyzing multi-modal sequencing datasets, including DNA and RNA
• Expertise in statistical genetics, computing polygenic risk scores using published methods and adapting or extending these methods for novel applications
• Expertise in building probabilistic statistical models that explicitly account for uncertainty, prior information, and incomplete observations
• Comfort operating in fast-moving, ambiguous startup environments with high ownership and accountability

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 $146,000 - $209,000. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL122 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL122's good faith estimate as of the date of publication and may be modified in the future.

COMPANY DESCRIPTION

Flagship Pioneering is a bioplatform innovation company that invents and builds companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health, sustainability and beyond exponentially accelerate scientific progress in areas ranging from disease detection and treatment and nature-positive agriculture to novel applications of AI that are driving the creation of new technologies.   

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

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

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

THE ROLE

We are seeking a Senior Scientist to lead the design, characterization, and performance optimization of aerosolizable particle systems. This role will be responsible for developing a foundational understanding of how engineered particles behave during generation, dispersion, and transport in air, and translating that understanding into robust, scalable material and system designs.

The Senior Scientist will operate at the interface of materials science, aerosol physics, and experimental engineering — owning the development of aerosol testing capabilities, guiding experimental strategy, and linking particle design to airborne performance. This individual will play a critical role in shaping early technical direction, establishing core methodologies, and driving progress from concept through validation.

This is a highly cross-functional role, working closely with formulation, process development, and hardware teams to ensure tight integration between particle design, production methods, and real-world deployment constraints.

KEY RESPONSIBILITIES

• Lead the design and optimization of particle systems for aerosolization, with ownership over key parameters including size distribution, morphology, density, and dispersibility;
• Develop and scale experimental capabilities for aerosol generation and testing, including selection, design, and validation of dispersal systems and measurement tools;
• Define and execute experimental strategies to understand relationships between particle properties, environmental conditions, and airborne behavior;
• Characterize aerosol performance using appropriate instrumentation (e.g., particle sizers, optical counters, flow diagnostics), and translate findings into design rules and system improvements;
• Develop and apply computational approaches to model aerosol physics and particle dispersal, integrating atmospheric transport and dispersion models or Lagrangian particle simulations with experimental data to inform particle and system design;
• Collaborate cross-functionally with formulation and process development teams to align particle production methods with aerosol performance requirements;
• Establish best practices, workflows, and technical standards for aerosol experimentation, including calibration, reproducibility, and data quality;
• Interpret complex datasets and communicate insights clearly to guide technical and strategic decision-making;
• Contribute to system-level thinking around particle generation, dispersion, and scale-up, incorporating constraints from real-world operating environments;
• Mentor junior scientists and contribute to building a strong experimental and technical culture within the team.

PROFESSIONAL EXPERIENCE & QUALIFICATIONS 

• PhD in aerosol science, chemical engineering, mechanical engineering, physics, materials science, or a related discipline, with 5+ years of relevant industry or applied research experience (or Master’s/Bachelor’s with significant additional experience);
• Deep expertise in aerosol science, including particle generation, transport, and measurement, with a strong understanding of how particle properties influence airborne behavior;
• Hands-on experience with aerosol instrumentation (e.g., SMPS, APS, optical particle counters) and the ability to design and interpret complex experiments;
• Strong foundation in transport phenomena, fluid dynamics, and particle physics as applied to airborne systems;
• Experience working with particulate materials, including connecting physical properties (size, shape, density, surface characteristics) to performance outcomes;
• Experience with modeling aerosol transport and dispersion using Lagrangian particle dispersion models, computational fluid dynamics (CFD) simulations, or related numerical approaches is a strong plus;
• Demonstrated ability to design experimental systems and build or adapt setups for aerosol generation and testing;
• Proven ability to lead technical projects in fast-paced, early-stage environments, balancing hands-on work with strategic thinking;
• Strong communication and documentation skills, with the ability to synthesize complex technical findings into clear, decision-relevant insights;
• Demonstrated curiosity, adaptability, and comfort working across disciplines to translate early-stage scientific ideas into functional systems.

LOCATION:  Cambridge, MA

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-TL1

The salary range for this role is $126,000 - $159,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Protocos currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Protocos'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.

Company Summary:

Serif Biomedicines, Inc. is a privately held, early-stage biotechnology company developing a novel approach to gene therapy that can address currently untreatable diseases.

Serif Biomedicines was founded by Flagship Pioneering, an innovation enterprise that conceives, creates, resources, and grows first-in-category life sciences companies.

Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA), Syros Pharmaceuticals (SYRS), Seres Therapeutics (NASDAQ:MCRB), Generate Biomedicines, Tessera Tx, Evelo Biosciences (EVLO), and Indigo Agriculture.

The role

We are seeking a highly innovative and driven Senior Scientist, Molecular Biology to lead the design and generation of next-generation DNA constructs enabling programmable medicines. This role is ideal for a scientist who thrives at the intersection of synthetic biology, high-throughput cloning, and computational sequence engineering.

You will play a critical role in building scalable platforms for plasmid DNA design, construction, and optimization, leveraging automation, algorithm-driven sequence design, and data-centric workflows. The ideal candidate brings deep technical expertise, creative problem-solving, and a passion for pushing the boundaries of nucleic acid engineering in a fast-paced, entrepreneurial environment.

The Senior Scientist will report to the Director of Molecular Biology and is expected to manage a direct report.  The role involves close collaboration with other Scientists and group leads across the company as part of a highly collaborative and growing R&D group.

Key responsibilities

• Lead the end-to-end design and construction of plasmid DNA constructs, including vector architecture, gene synthesis strategies, and high-efficiency cloning workflows (e.g., Gibson, Golden Gate, recombination-based methods).
• Drive automated and computational sequence design, utilizing advanced tools and pipelines for codon optimization, regulatory element tuning, and multi-parameter construct optimization.
• Establish vendor relationships with an emphasis on hybrid internal and external capabilities to remain agile while minimizing the impact on project timelines.
• Develop and implement variable-throughput cloning and screening platforms, standardized workflows, and scalable molecular biology processes.
• Own sequence analysis pipelines, variant analysis, and construct QC.
• Collaborate cross-functionally with diverse teams in the company. The ideal candidate will have a direct relationship with CMC. The chosen candidate will provide designs, material and timelines to CMC, as requested.
• Mentor and guide junior scientists, establishing best practices in molecular biology, experimental design, and data rigor.
• Establish a rigorous ELN environment including sample management, version-controlled sequence design, and reproducible research practices.
• Communicate scientific insights effectively, presenting results across functional teams and leadership to drive strategic decision-making.

Who you are

We encourage all candidates with exemplary experience in related fields to apply.

Technical Expertise

• PhD with 5+ years of relevant experience in relevant scientific discipline (Molecular Biology, Synthetic Biology, Bioengineering).
• Deep expertise in molecular cloning, plasmid design, DNA construct engineering, and E. coli strain engineering, including genetic modification and expression system development.
• Demonstrated experience with automated sequence design tools, scripting (e.g., Python), and/or computational biology workflows.
• Strong background in high-throughput and scalable molecular biology techniques.
• Experience with NGS data analysis and sequence validation pipelines.
• Familiarity with lab automation platforms and workflow integration is a plus.

Leadership & Collaboration

• Proven ability to lead complex projects and influence cross-functional teams.
• Strong mentorship skills with commitment to developing others. Previous technical or professional management experience.
• Excellent communication skills, with the ability to translate complex ideas across disciplines.

Values and Behaviors:

Flagship is an experiment in institutional, entrepreneurial, and innovation practiced in the context of a small company with an insurgent mindset. We are seeking individuals with an entrepreneurial spirit, strong communication skills, and comfort in working in and contributing to a dynamic and cross-functional team environment.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, we encourage you to apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background. The level of the role will be commensurate with the education and years of experience of the identified candidates.

Flagship Pioneering and our ecosystem companies are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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 - $181,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL87 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL87's good faith estimate as of the date of publication and may be modified in the future.

The Company

Flagship Labs 110 Inc. (FL110) is a privately held, early-stage technology company developing a fully integrated, end-to-end platform to enable next generation proteomics. Our platform integrates groundbreaking innovations in bioengineering, machine learning, and custom microelectronics to offer a level of precision and insight never before achieved.

FL110 is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. We are uniquely cross-functional and collaborative. Our teams thrive in unstructured and creative environments. Therefore, we seek individuals with an inclusive mindset and a diversity of thought.

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply.

The Role:

FL110 is seeking a creative and talented (Senior) Scientist, Nanopore to join our team. Leveling is flexible based on experience. This role will focus on developing nanopore sensing technologies and will join a team creating a nanopore based protein reading system.

You will be part of a dynamic, cross-functional team, working closely with chemists, bioinformaticians, software developers, and hardware engineers. The ideal candidate has a strong background in nanopore technology, specifically with protein translocation, as well as either experience in biotech industry or a record of scientific achievement.

Key Responsibilities

• Conduct advanced research in nanopore technology to drive technological advancements and deliver impactful results
• Develop and implement innovative research strategies and methodologies
• Collaborate with cross-functional teams to align research activities with company objectives
• Manage resources and timelines effectively
• Foster a culture of innovation and scientific excellence within the team
• Collaborate with internal and external stakeholders, including academic institutions, industry partners, and regulatory bodies
• Present research findings at scientific conferences and contribute to patent applications
• Communicate complex scientific concepts and project updates to diverse audiences, including non-scientific stakeholders

Basic Qualifications

• Ph.D. in Physics, Molecular Biology, or related field
• Demonstrated experience in nanopore experimentation and protein translocation
• Experience with python-based data analysis and R
• Proven track record of scientific achievements demonstrated through publications, patents, and successful project completions
• Strong leadership and project management skills
• Excellent problem-solving abilities, analytical skills, and attention to detail
• Strong communication skills, both written and verbal, with the ability to convey complex scientific information to diverse audiences
• Ability to work independently and collaboratively in a fast-paced, dynamic environment

Nice-to-Haves

• Demonstrated expertise in protein biochemistry including protein expression and purification

Who Will Love This Job

• A rigorous individual with a curious mind and a love of learning who enjoys working in a fast-paced environment with a driven and collaborative team

About Flagship Pioneering

Flagship Pioneering is a bioplatform innovation company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.  Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com.

Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.

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 $100,000 - $181,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. FL110 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL110's good faith estimate as of the date of publication and may be modified in the future.

Are you driven by data, inspired by innovation, and eager to shape the future of insurance?

Join a fast-growing Canadian P&C insurer where you'll play a pivotal role in advancing our Actuarial Services function. We're building on a solid foundation—powered by cutting-edge technology, a robust enterprise data analytics team, and bold investments in AI. With this groundwork in place our talented team is now focused on scaling and refining our capabilities.

We're looking for bright, analytical minds to help bring our strategy to life. If you're passionate about solving complex problems and want to explore Pricing, Underwriting, and Claims, we want to hear from you.

Senior Data Scientist

We're looking for a Senior Data Scientist to join our growing team and build the next generation of predictive analytics solutions. In this role, you won’t just be crunching numbers, you’ll be using machine learning (ML) and artificial intelligence (AI) models to transform raw data into powerful insights that drive our business forward.

This is an opportunity to directly contribute to our core operations, working alongside a supportive team who are invested in your growth. If you have a passion for data and a desire to see your work make a tangible impact, this role is for you.

What you'll do:

• Deliver value through data-driven algorithms and models: You will apply the right mix of ML and AI to solve high-impact business problems. You’ll partner with stakeholders to select and defend the best model architecture and explainability approaches to balance performance, interpretability, and trade-offs.
• Embed ML/AI into core business capabilities: You will build deep expertise in P&C insurance workflows and translate that knowledge into practical ML/AI-powered analyses, decision tools, and visualizations that improve how work gets done.
• Partner with stakeholders to ensure adoption, value, and model integrity: You’ll align with stakeholders on goals and success metrics, then pressure-test solutions against real constraints to ensure they’re feasible and valuable. You will communicate your insights and recommendations with clarity and confidence to both technical and non-technical audiences.
• Invest in Your Future: We're committed to your professional development. You'll engage in project-specific research to continually grow your skills and have the unique opportunity to collaborate with our Claims and Finance departments.

 What You’ll Need to Succeed

• Education: You have a master’s degree in a quantitative or technical discipline
• Experience: You have 3–5 years of experience in an ML/AI development role, with experience deploying ML / AI models into production and associated governance procedures.
• Technical Skills: You have a broad understanding of modern ML architectures, familiarity with cloud and ML platforms. You have strong Python programming skills and experience with various ML libraries.
• Core Competencies: You have excellent analytical, quantitative, and critical thinking skills. You are highly analytical and use your communication and collaboration skills to engage with stakeholders to solve problems.

If you're ready to be a core part of our mission and make a tangible impact from day one, we want to hear from you.

#LI-Hybrid

The expected base salary range for this position is $79,500 - $129,500. Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary. You have the potential to earn more through Gore Mutual’s discretionary bonus program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.

Please note: This range reflects the expected base salary for this role but may not represent the full compensation range for all experience and skill levels. During the recruitment process, we will discuss and consider how your unique qualifications align with the broader range for this position.

Gore Mutual is proud to offer a comprehensive total rewards package which includes extended health and dental benefits, disability insurance, retirement plan matching, paid time off, recognition and perk programs.

Position Overview

We are seeking a Scientist II/ Senior Scientist I with hands‑on experience in phase‑appropriate analytical method development, optimization, qualification, and transfer to support the release, stability, and characterization of cell and gene therapy products. This role will mainly support Beam’s in vivo lipid nanoparticle (LNP) based programs and will be based in a laboratory environment.

The ideal candidate will have experience in design and development of analytical methods for mRNA, gRNA, protein, protein conjugate, lipid, and LNP, experience working collaboratively with cross-functional research and CMC teams, and have a working knowledge of analytical ICH/USP guidelines.

Primary Responsibilities:

• Lead early through late phase method development, optimization, and transfer for lot release, stability, and characterization of drug substances, critical materials, and drug products.
• Establish technical leadership as subject matter expert in multiple analytical techniques during method development and transfer and provide technical troubleshooting support when needed.
• Work with cross-functional groups including Research & Development, Quality Control, and Process Development teams to participate in various aspects of method development, transfer, characterization, comparability, and investigation.
• Coordinate routine sample testing including requests from Research and Development groups and Process Development teams.
• Author and review SOPs, technical reports, and assist in the preparation of CMC regulatory submissions.
• Analyze, track, and trend data to monitor analytical assays and ensure consistency in assay performance.
• Maintaining detailed documentation of experiments in ELN system.
• Adapting to a fast-paced, dynamic research environment.
• Mentor and train junior scientists
• Living Beam Therapeutics core values of being part of a community of fearless innovators, being rigorous and honest in our research, listening with open minds, and committed to each other.

Qualifications:

• Degree in a relevant discipline (biochemistry, biotechnology, biological sciences, bioengineering, or related fields). Minimum PhD with 2+ years or BS/MS with 10-15 years (title based on experience) industry experience including biotech, biopharma, CRO, and CDMO.
• Must have hand on experience on analytical method development, optimization, qualification, and testing at GMP or non-GMP environments, supporting clinical phase programs.
• Experience with analysis of RNAs, proteins, protein conjugates, lipids, and lipid nanoparticles (LNPs) is highly desirable and will be key to success in this role.
• Extensive experience with at least one or several of the analytical techniques is required: HPLC (RP, IPRP, SEC, IEX), capillary gel electrophoresis, ELISA. Experience with qPCR, DNA and RNA extraction, western blotting, UV spectrophotometry, DLS, MALS, mass spectrometry, and compendial testing will be a plus.
• Experience with analytical CMC development, method transfer, and QC technical support is highly desirable.
• A good understanding of ICH Q2 and Q14, with working knowledge on analytical Quality by Design concept.
• CMC project management and people management experience will be a plus.
• Familiarity with data analysis software such as Openlab, Chromeleon, and statistical software such as JMP.
• Team player with excellent oral and written communication skills.
• Independently motivated, detail-oriented scientist with excellent critical thinking and problem-solving abilities.
• Excellent organizational skills towards multi-tasking in an extremely fast-paced environment with changing priorities.
• Must be able to work onsite daily

Why Join Us?

Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines that unlock 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?

Parabilis Inc. is seeking a highly talented and motivated Senior Data Scientist / Cheminformatician to support the platform discovery engine for Helicon^TM peptide drugs. Reporting to the Associate Director of Cheminformatics, the candidate will work collaboratively with biologists and chemists, leveraging skills in data science and cheminformatics to enable hypothesis generation and data insights for advancing Fog preclinical drug discovery.

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 data 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 platform.

Responsibilities

• Provide scientific leadership and data science / (chem)informatics expertise towards, but not limited to, hit identification, targeted screening of Helical peptide library designs, hit prioritization, hit-to-lead progression using multi-objective optimization, new drug-target assessments, and advancing drug-pipeline projects towards the clinic
• Analyze peptide/chemical structure and property space to identify patterns / gaps that inform Helicon and monomer designs
• Adapt and implement data analytics and machine learning techniques towards predictive models of Helicon^TM properties
• Contribute to implementation and development of cheminformatics and research informatics systems and tools for Fog
• Work with IT and data engineering to enable enterprise-level cheminformatics solutions

Requirements

• MS or PhD in Data Science, Cheminformatics, Computational Chemistry or Computational Biology, Chemistry, Biophysics, Macromolecular sciences, Computer Science, or related scientific field with 5+ years of experience within the pharmaceutical or biotechnology field
• Proven track record of impact in a drug discovery program using informatics/computational techniques
• Demonstrated expertise with cheminformatics (e.g. RDKit, ICM, OEChem) and data science toolkits/libraries (e.g. Pandas, Scikit-Learn, and Numpy)
• Demonstrated understanding of critical assessment of molecule-property data and predictive model quality
• Demonstrated expertise in data analytics and solid grasp of statistical principles
• Experience with data visualization techniques and exploration tools (e.g Vortex, Spotfire, Datawarrior, DataGrok)
• Strong scientific programming skills (Python). Familiarity with modern pipeline tools is a plus.
• Excellent communication and collaboration skills that contribute to and inspire a vibrant community of drug hunters
• Experience with (chem)informatics analyses of peptides, machine learning, databases/enterprise informatics systems (e.g. Dotmatics), or cloud computing environments (e.g. Google, AWS, Azure) is a 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 Medicines 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.

About the Role:

Stylus Medicine is seeking an intellectually curious and collaborative Senior Scientist, who will lead the development of upstream microbial fermentation processes as part of our CMC Tech Ops team. This role will be responsible for process definition, development, characterization, scale-up and tech transfer from bench scale to pilot. Working closely with the Research, Preclinical, and Formulation teams, this is a special opportunity to advance the development of transformative in vivo genetic medicines.

Key Responsibilities & Accountabilities:

• Develop scalable production processes for nucleic acids and recombinant proteins
• Leverage expertise in fermentation and mammalian cell culture to design, optimize, scale-up and characterize production processes
• Independently utilize multivariate design of experiment (DoE) approaches to improve productivity and optimize parameters for product quality
• Drive fermentation platform development and new technology implementation to improve process performance, generation of predictive process models, and enhance process control and robustness
• Design and implement in-process analytics to improve productivity while reducing process and product derived impurities
• Maintain and troubleshoot equipment to ensure consistency and continuity of operations
• Document, analyze and present experimental results internally and externally
• Partner with CDMOs and provide technology transfer support to facilitate scale up
• Interface with cross-functional teams to ensure programs are on track and stakeholders’ needs are met
• Maintain accurate and reliable record keeping including database management, batch records, notebooks, and all other pertinent documentation

Qualifications & Skills:

• PhD in Chemical/Biomedical Engineering, Biochemistry, Pharmaceutical Sciences, or related discipline with >4 years of experience, or BS/MS with >8 years of experience in biopharmaceutical or biotechnology development, including experience in developing scalable fermentation processes for producing plasmid DNA and/or recombinant products
• In-depth experience and knowledge in fermentation process development, optimization, and process scale-up / scale-down model development
• Familiarity with strain engineering and biocatalysis
• Familiarity with performing operations in a cleanroom environment, applying controls to ensure aseptic processing
• Demonstrated ability to coach and mentor junior researchers
• Independently motivated and good problem-solving ability
• Attention to detail and accuracy in developing, reviewing, and following protocols, SOPs, batch records and technology transfer documents is a must
• Demonstrated ability to work collaboratively across teams to meet project deliverables and timelines
• Strong communication, decision-making and organizational skills
• Proficiency with statistical analysis software (e.g., JMP) is highly desired
• Prior experience partnering with external CDMOs and conducting tech transfers preferred

Pay Range: $155,000 - $170,000

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.

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