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

FL94 Inc., is a privately held, early-stage biotechnology company pioneering Protein Editing. At FL94 we create small molecules that edit protein structure and function to unlock presently undruggable targets and a broad array of novel chemistry modalities. Our platform integrates novel small molecule chemistry and chemoproteomic discovery technologies with machine learning to enable generative design of protein editing chemistries. FL94 is backed by Flagship Pioneering, bringing the courage, vision, and resources to guide FL94 from platform validation to patient impact. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us! 

We are building a data generation platform of unprecedented quality, relevance, and quantity to build a foundational approach to generative chemistry design.  

FL94 is backed by Flagship Pioneering, bringing the courage, vision, and resources to guide FL94 from platform validation to patient impact, just as Flagship Pioneering previously accomplished with Moderna.. We are seeking collaborative, relentless problem solvers that share our passion for impact to join us! 

Position Summary: 

FL94 is seeking a talented (Senior) Machine Learning Scientist. The successful candidate will develop and apply cutting-edge machine learning (ML) paradigms across FL94’s proprietary chemoproteomics and small molecule chemistry data sets to narrow the search space and increase the probability of discovering novel chemistries via generative design. This position is ideal for someone with demonstrated depth of expertise in training deep learning models on chemical or molecular structures. 

Key Responsibilities: 

  • Translate small molecule and proteomic drug discovery challenges into ML problems 
  • Maximize value of public and proprietary data assets 
  • Develop, prototype, and produce novel ML algorithms for impactful drug discovery problems 
  • Train and validate large deep learning models at scale
  • Leverage open-source deep learning models, data sets, and transfer learning to reduce time to solution
  • Speed up training of large deep learning models using clusters of CPUs and GPUs
  • Develop optimized data pipelines to fuel train deep learning models
  • Collaborate closely with experimental biologists, proteomics, chemists and computational biologists to focus efforts on impactful problemso build data pipelines for ingesting high throughput experimental data
  • Communicate findings to a multi-disciplinary audience 


  • PhD in applied mathematics, machine learning, computer science, or and other quantitative disciplines with a strong focus in machine learning and deep learning (candidates with experience training graph neural networks are encouraged to apply) 
  • Proven track record of innovation in applied mathematics, data science and ML 
  • 5-10+3+ years hands-on experience in implementing, evaluating and tuning hyperparameters for large deep learning models such as GNNs, CNNs, RNNs, Transformers, VAEs, and diffusion models 
  • Strong expertise in multiple programming paradigms and software libraries (e.g.such Python, JAX, Tensorflow, (or Pytorch), Keras, Pandas, Sklearn, Hugging Face)
  • Experience using AWS services such as S3, EC2, ECS, AWS Batch, Sagemaker to reduce runtime to train and evaluate deep learning models
  • Experience in biotech/pharma, or small molecule drug design is ideal but not required. Candidate must have experience in solving real world problems using deep learning in a multidisciplinary setting.
  • Foundational understanding of biology and chemistry is ideal, but not required.
  • Strong written and oral communication skills 

Location: Cambridge, MA 

More About Flagship Pioneering

Flagship Pioneering conceives, creates, resources, and develops first-in-category life science platform companies to transform human health and sustainability. Since its launch in 2000, the firm has, through its Flagship Labs unit, applied its unique hypothesis-driven innovation process to originate and foster more than 100 scientific ventures, resulting in over $100 billion in aggregate value. To date, Flagship has deployed over $3.1 billion in capital toward the founding and growth of its pioneering companies alongside more than $19 billion of follow-on investments from other institutions. The current Flagship ecosystem comprises  transformative companies, including  Moderna (NASDAQ: MRNA), Sana Biotechnology (NASDAQ: SANA), Seres Therapeutics (NASDAQ: MCRB), Axcella Health (NASDAQ: AXLA), Denali Therapeutics (NASDAQ: DNLI), Foghorn Therapeutics (NASDAQ: FHTX), Indigo Ag, Generate Biomedicines, Tessera Tx, and others.

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.

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