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Senior Machine Learning Engineer
Senior Machine Learning EngineerFlagship Pioneering • Boston, Massachusetts, United States
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Senior Machine Learning Engineer

Senior Machine Learning Engineer

Flagship Pioneering • Boston, Massachusetts, United States
[job_card.30_days_ago]
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  • [job_card.full_time]
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About ProFound Therapeutics

ProFound Therapeutics is pioneering the discovery of the expanded human proteome to unlock a new universe of potential therapeutics. By integrating multi-omics, advanced computation, and translational biology, we aim to reveal and characterize thousands of previously uncharted proteins and systematically explore their role in health and disease.

The Role

We are seeking a highly motivated Senior Machine Learning Engineer / Data Scientist to join our AI / ML team. This individual will play a central role in designing and implementing advanced machine learning systems that integrate multi-omics, perturbation, and biological knowledge graph data. Working closely with the Head of AI / ML and cross-functional partners, you will develop generative, transformer-based, and causal models — including large language models (LLMs) — within a multi-agent causal AI framework to uncover disease-driving proteins and pathways. The insights generated will directly support therapeutic discovery and development.

Key Responsibilities

  • Architect and implement scalable ML systems that integrate multi-modal data (genomics, transcriptomics, proteomics, imaging, perturbation data).
  • Develop and deploy graph-based, transformer-based, and generative models (including LLMs) to capture biological relationships and simulate interventions.
  • Contribute to building a multi-agent causal AI framework that integrates causal graph learning, intervention simulation, and knowledge graph reasoning.
  • Collaborate with data engineering teams to design data pipelines that harmonize and prepare large-scale omics datasets for model training.
  • Implement, evaluate, and optimize causal inference methods (e.g., DAG learning, treatment-effect estimation, counterfactual modeling).
  • Partner with experimental scientists to ensure model outputs are biologically interpretable and experimentally testable.
  • Stay abreast of advances in ML / AI, causal modeling, and computational biology; bring innovative ideas into the team.

Qualifications

  • Ph.D. or M.S. in Computer Science, Physics, Computational Biology, Biostatistics, Applied Mathematics, or related field, with 3+ years of relevant post-graduate or industry experience.
  • Proven track record in machine learning model development, with expertise in transformers, graph neural networks, generative modeling, or causal inference.
  • Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, JAX, or PyTorch Geometric.
  • Experience working with multi-omics or high-dimensional biological data is strongly preferred.
  • Strong background in probabilistic modeling, causal reasoning, or statistical inference.
  • Familiarity with knowledge graph technologies and graph databases is a plus.
  • Demonstrated ability to work in cross-disciplinary teams, communicate complex ideas clearly, and deliver results in fast-moving environments.
  • Values and Behaviors

    We are seeking individuals with an entrepreneurial spirit, strong communication skills, and comfort working in and contributing to a dynamic and cross-functional team environment. The level of the role will be commensurate with the education and years of experience of the identified candidate.

    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.

    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 .

    If your experience is close to what we’re looking for, please consider applying. Experience comes in many forms, skills are transferable, and passion goes a long way. We know that diverse backgrounds and experiences make for the best problem-solving and creative thinking, which is why we’re dedicated to adding new perspectives to the team and encourage everyone to apply. We look forward to learning more about you.

    We 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.

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