Machine Learning Scientist

Posted 7 Days Ago
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Somerville, MA, USA
In-Office
132K-209K Annually
Mid level
Biotech
The Role
Develop and fine-tune foundation, generative, and perturbation models for single-cell and other biological data to support disease modeling, target identification, and drug discovery. Build interpretable models, deploy generative AI on cloud platforms, establish benchmarking frameworks, and collaborate with biology, chemistry, and omics researchers. The role also involves communicating technical concepts and may include developing agentic AI systems for scientific discovery.
Summary Generated by Built In

What if you could join a rapidly growing company and play a critical role in bringing new medicines to patients through looking at and treating disease in a revolutionary way.

What this position is all about:

We seek a Machine Learning Scientist to join our ML team and lead focused efforts in applying and adapting proprietary foundation models to enable Cellarity’s predictive drug discovery platform. As a lead ML Scientist the candidate will develop and apply AI methods to identify novel interventions and targets to accelerate early drug discovery.

This role involves hands-on modeling of high-dimensional biological data, leveraging and fine-tuning state-of-the-art foundation models, while enabling interpretability and biological reasoning. Ideal candidate will have demonstrated application of deep learning and computational biology to biological problems.

The successful candidate will work closely with researchers in biology, chemistry, and omics technology in a collaborative environment.

What you would be responsible for:

  • Model Development

    • Apply, fine-tune, and post-train foundation models (e.g., transformer-based, diffusion, VAE architectures) on single-cell RNA-seq data and other modalities to model disease cellular states
    • Build state-of-the-art perturbation models using multi-modal perturbation data (small molecules, CRISPR, cytokines) and phenotypic data, with emphasis on CRISPR screen data (e.g., Perturb-seq).
    • Develop mechanistic interpretability methods to infer gene networks and regulatory mechanisms via attention, graph-based, and/or causal representation methods, supporting downstream applications such as target identification.
    • Deploy and run inference on generative AI models using proprietary datasets on cloud platforms.
    • Establish clinically relevant benchmarking and evaluation frameworks to assess context generalization and guide model improvements.
    • Stay current with the latest research in foundation models, representation learning (across biology, NLP, vision, and audio), and perturbation modeling.

    Scientific Collaboration

    • Collaborate with interdisciplinary scientists from biology, chemistry, and technology teams to translate research questions into cutting-edge ML solutions.
    • Opportunity to collaborate with and co-develop platform modules alongside other Flagship Pioneering companies.
    • Communicate technical concepts clearly to diverse scientific audiences.

What experiences will you need:

  • PhD in Computer Science, Computational Biology, or related field, OR Master's degree with 3+ years or Master's or Bachelor's degree with 6+ years of relevant ML research experience for drug discovery.
  • Strong foundation in statistics, deep learning and generative AI.
  • Experience with high-dimensional biological data analysis (bulk/single-cell RNA-seq, gene regulatory networks, PPI networks, multi-omics integration).
  • Experience with chemical / CRISPR perturbation screen data (e.g., Perturb-seq), including analysis and modeling.
  • Familiarity with single-cell foundation models (e.g., Geneformer, scGPT, scFoundation) and their downstream applications.
  • Experience applying or fine-tuning pretrained foundation models or deep generative models for downstream biological tasks.
  • Experience with cloud computing (AWS/GCP) and MLOps best practices.
  • Excellent communication skills and ability to work in interdisciplinary teams.

What sets you apart:

  • Experience building agentic AI systems (e.g., LLM-based agents, tool use, multi-step reasoning workflows) for scientific discovery or data analysis.
  • Familiarity with target identification and prioritization in drug discovery.

What it’s like to work at Cellarity
At Cellarity, we

  • Push Boundaries: We create a legacy with breakthrough science in service of patients.
  • Inject Energy: We build strengths from different perspectives and tell it like it is
  • Own it: We transcend our job descriptions and relentlessly follow through on our commitments.
  • Go all out: We work quickly and with conviction.

Company Summary: Cellarity is a privately held, clinical-phase drug discovery startup using AI and single-cell omics to develop life-changing medicines that are unreachable by traditional methods of drug discovery. Our pipeline spans multiple exploratory programs across different indications, offering broad opportunities to apply machine learning to diverse disease areas. Cellarity is a product of Flagship Pioneering's venture creation engine, which has conceived and created companies such as Moderna (NASDAQ: MRNA), Generate:Biomedicines, and Lila Sciences.

Cellarity 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.

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

The salary range for this role is $132,000 - $209,000. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Cellarity currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Cellarity's good faith estimate as of the date of publication and may be modified in the future.


Privacy Notice for Applicants: When you apply for a role at Flagship Pioneering or one of its portfolio companies, we collect and use personal information you provide (such as your name, contact details, work history, and application materials) to evaluate your application, communicate with you, and comply with legal obligations. Your application data is processed through Greenhouse, our applicant tracking system, and may also be reviewed using AI-assisted screening tools. We do not sell your personal information. California residents have rights under the CCPA/CPRA including to know, delete, and opt out of the sharing of their personal information. If you are located in the EU or UK, we process your data under GDPR and you have rights to access, rectify, and erase your data. To exercise your rights or for questions, contact [email protected]

Skills Required

  • PhD in Computer Science, Computational Biology, or a related field
  • Master's degree with 3+ years of relevant machine learning research experience for drug discovery
  • Bachelor's or Master's degree with 6+ years of relevant machine learning research experience for drug discovery
  • Strong foundation in statistics, deep learning, and generative AI
  • Experience analyzing high-dimensional biological data, including bulk or single-cell RNA-seq
  • Experience with gene regulatory networks, protein-protein interaction networks, and multi-omics integration
  • Experience analyzing and modeling chemical or CRISPR perturbation screen data, including Perturb-seq
  • Familiarity with single-cell foundation models such as Geneformer, scGPT, or scFoundation
  • Experience applying or fine-tuning pretrained foundation models or deep generative models for biological tasks
  • Experience with cloud computing, including AWS or GCP
  • Experience with MLOps best practices
  • Excellent communication skills and ability to work in interdisciplinary teams
  • Experience building agentic AI systems, including LLM-based agents, tool use, or multi-step reasoning workflows, for scientific discovery or data analysis
  • Familiarity with target identification and prioritization in drug discovery

Flagship Pioneering Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Flagship Pioneering and has not been reviewed or approved by Flagship Pioneering.

  • Fair & Transparent Compensation Feedback suggests salary bands are visible for many Boston/Cambridge roles and pay is considered competitive for key scientific and leadership positions. Transparency in postings supports expectations that offers align with local biotech norms.
  • Healthcare Strength Feedback suggests medical, dental, vision, disability, life insurance, HSA options, and mental-health coverage are comprehensive and well-regarded. Multiple items are employer-verified, reinforcing confidence in core health benefits.
  • Parental & Family Support Feedback suggests maternity/paternity leave and family leave are offered at meaningful levels. These programs sit alongside paid holidays, sick days, and PTO to support family needs.

Flagship Pioneering Insights

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The Company
HQ: Cambridge, MA
475 Employees
Year Founded: 2000

What We Do

Flagship Pioneering conceives, creates, resources, and develops first-in-category life sciences companies to transform human health and sustainability. Since its launch in 2000, the firm has applied a unique, hypothesis-driven innovation process to originate and foster more than 100 scientific ventures, resulting in over $30 billion in aggregate value. To date, Flagship is backed by >$3 billion of aggregate capital commitments, of which over $1.5 billion has been deployed toward the founding and growth of its pioneering companies alongside >$10 billion of follow-on investments from other institutions. The current Flagship ecosystem includes Denali Therapeutics (NASDAQ: DNLI), Evelo Biosciences (NASDAQ: EVLO), Moderna Therapeutics (NASDAQ: MRNA), Rubius Therapeutics (NASDAQ: RUBY), Seres Therapeutics (NASDAQ: MCRB), and Syros Pharmaceuticals (NASDAQ: SYRS).

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