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Senior ML Scientist, Biomolecule Design; Protein​/RNA​/DNA

Job in Cambridge, Middlesex County, Massachusetts, 02140, USA
Listing for: Flagship Pioneering
Full Time position
Listed on 2026-05-29
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer
  • Research/Development
    Data Scientist
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Position: Senior ML Scientist, Biomolecule Design (Protein/RNA/DNA)

FL97 is seeking an experienced, creative, and talented (Senior) Machine Learning Scientist, Biomolecule Design to join our team. You will be part of an agile, cross-functional team responsible for generating protein, RNA or DNA sequences, updating models with experimental data, and integrating ML models into the data pipelines for our labs. Together with biologists, bioinformaticians, software developers, and automation engineers, you will work toward modeling biological sequences across a variety of valuable therapeutic applications.

The ideal candidate has a machine learning background with biotech industry experience building generative ML models, pre-processing pipelines, and comprehensive benchmarks to support biological sequence design.

Candidates should have experience and interest in:

  • Designing, training and fine-tuning deep learning models to engineer proteins, RNA or DNA.
  • Implementing rigorous testing, documentation, and model benchmarking.
  • Incorporating these models into AI-enabled tool chains for the biology lab.
  • Collaborating with cross-functional teams to translate ML model predictions into evaluated sequences by the wet lab.

Qualifications:

  • PhD in applied mathematics, computer science, physics, computational biology or other quantitative disciplines.
  • Proven track record in developing deep learning models.
  • Experience with large language models (e.g. autoregressive LLMs) for biological sequences.
  • Expertise in at least one ML framework (PyTorch/Tensor Flow/Jax) and robust experience in the Python data science ecosystem.
  • Experience in training and deploying ML models on distributed computing services

Working at FL97, you would have access to advanced technology in the areas of:

  • AI experimental design and simulation
  • Automated liquid handling and instrumentation
  • Generative molecular design

More About Flagship Pioneering

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

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.

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.

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Position Requirements
10+ Years work experience
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