(Senior) Machine Learning Scientist

Flagship Pioneering, Inc.
Watertown +1 more
On-site

Who this role is best for

Geared toward candidates with a strong background in molecular modeling and a collaborative mindset, comfortable with building and shipping predictive models for ADMET and potency.

Best fit for

  • Candidates with a PhD in computational chemistry or machine learning and experience in molecular modeling
    — “PhD in computational chemistry, cheminformatics, machine learning or a related field”
  • Individuals with a track record of deploying ML models in industry or academia for molecular endpoints
    — “Demonstrated experience training and validating ML models on chemical or molecular data, in industry or academia, with shipped or published results”
  • Professionals who can translate complex ML results into actionable insights for chemists and biologists
    — “Present results and limits of each model to chemists and project teams, and incorporate their feedback into retraining”

Things to consider

  • The role requires fluency with molecular representations and cheminformatics tools like RDKit
    — “Fluency with molecular representations (fingerprints, descriptors, graphs, 3D) and tools such as RDKit”
  • Experience with graph neural networks or equivariant models is a key technical requirement
    — “Experience with GNNs or transformers on molecules”
  • The position demands rigorous evaluation practices, including handling noisy data and uncertainty estimation
    — “Rigorous evaluation habits: scaffold or temporal splits, baselines, noisy-label handling and uncertainty estimation”

How to stand out

  • Emphasize published models or industry contributions in molecular ML on your resume
    — “Publications, open-source contributions or competition results in molecular ML”
  • Highlight experience with specific molecular endpoints like ADMET or potency in your interview narrative
    — “Train and maintain ML models for ADMET and developability endpoints such as solubility, permeability, metabolic stability, toxicity and aggregation risk”
  • Showcase your ability to fine-tune structure-aware models with examples from your background
    — “Apply and fine-tune structure-aware models (GNNs, equivariant networks, protein-ligand structure and docking-informed ML)”
  • Demonstrate your experience with model packaging and versioning for production use
    — “Package models for the platform with engineers: versioned, reproducible and monitored for drift”
Pace · SteadyCollaboration · MediumAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • two or three models in production use by project teams
  • documented benchmarks
  • calibrated uncertainty
  • clear applicability domain
Typical background
PhD in computational chemistry, cheminformatics, machine learning or a related field3-6 years of hands-on modeling experience

Skills & requirements

Required

Machine LearningModel TrainingValidationChemical MoleculesAdmetPotencySynthesizability3D StructureCurate And Clean Assay DataPackage ModelsCommunication With Chemists And Biologists

Preferred

PublicationsOpen-source ContributionsCompetition ResultsGenerative DesignActive LearningBayesian Optimization LoopsLarge-scale TrainingMlopsModel ServingDockingFree-energy MethodsProtein Structure Prediction Tools

Stack & domain

Machine LearningModel TrainingValidationProductionChemical MoleculesDevelopabilityPotencySynthesizability3D StructureAdmetQSARLigand-basedStructure-basedSynthetic AccessibilityReaction-outcome PredictionRetrosynthesis-informed FiltersStructure-aware ModelsGnnsEquivariant NetworksProtein-ligand StructureDocking-informed MLAssay DataScaffold- Or Time-split BenchmarksUncertainty EstimationPythonPyTorchTransformersMolecular RepresentationsFingerprintsDescriptorsGraphs3DRdkitMlopsModel ServingDockingFree-energy MethodsProtein Structure Prediction ToolsCommunicationTeamworkProblem-solvingInnovationAutomationProcess ImprovementBiotechnologyTherapeutic ModalityComputational ChemistryCheminformatics

About the role

Original posting from Flagship Pioneering, Inc. via Greenhouse

Company Overview:

Abiologics, Inc. is a privately held, early-stage biotechnology company on a mission to make biology better through an innovative therapeutic modality. We are pioneering the development of SynteinsTM, a transformational class of macromolecular medicines unlocked by novel synthetic and computational technologies. Abiologics is actively seeking exceptional molecular scientists who are passionate about driving therapeutic modality innovation in biotechnology.

Abiologics was founded in Flagship Pioneering’s venture creation engine, where companies such as Moderna Therapeutics (NASDAQ: MRNA) and Generate Biomedicines were conceived and created. Since Flagship’s founding in 2000, the firm has originated and fostered the development of more than 100 scientific ventures resulting in more than 500 issued patents and more than 50 clinical trials for novel therapeutic agents.

About the role:

We are hiring a Machine Learning Scientist to train, validate and ship the predictive models that power our molecular design platform. You will build models that score chemical molecules for developability (ADMET), potency, synthesizability and 3D structure, working alongside chemists, biologists and platform engineers.

In your first year, success means two or three models in production use by project teams, each with documented benchmarks, calibrated uncertainty and a clear applicability domain.

What you will do:

Train and maintain ML models for ADMET and developability endpoints such as solubility, permeability, metabolic stability, toxicity and aggregation risk.

Build potency and binding models (QSAR, ligand- and structure-based) to rank and prioritize molecules against targets.

Develop synthesizability models: synthetic accessibility scoring, reaction-outcome prediction and retrosynthesis-informed filters.

Apply and fine-tune structure-aware models (GNNs, equivariant networks, protein-ligand structure and docking-informed ML).

Curate and clean assay data, define scaffold- or time-split benchmarks, and quantify uncertainty and applicability domain.

Package models for the platform with engineers: versioned, reproducible and monitored for drift.

Present results and limits of each model to chemists and project teams, and incorporate their feedback into retraining.

What you bring:

PhD in computational chemistry, cheminformatics, machine learning or a related field, or an MS plus equivalent industry experience (about 3-6 years of hands-on modeling).

Demonstrated experience training and validating ML models on chemical or molecular data, in industry or academia, with shipped or published results.

Direct experience with at least two of: ADMET/developability, potency/binding, synthesizability/retrosynthesis, protein or ligand structure.

Fluency with molecular representations (fingerprints, descriptors, graphs, 3D) and tools such as RDKit.

Strong Python and a deep learning framework (PyTorch preferred); experience with GNNs or transformers on molecules.

Rigorous evaluation habits: scaffold or temporal splits, baselines, noisy-label handling and uncertainty estimation.

Clear communication with chemists and biologists.

Nice to have:

Publications, open-source contributions or competition results in molecular ML.

Experience with generative design, active learning or Bayesian optimization loops.

Experience with large-scale training, MLOps and model serving.

Familiarity with docking, free-energy methods or protein structure prediction tools.

Experience working with biologics or non-small-molecule modalities.

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 www.flagshippioneering.com.

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.

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.

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 privacy@flagshippioneering.com. 

The salary range for this role is $132,000 - $258,500. Compensation for the role will depend on a number of factors, including a candidate’s qualifications, skills, competencies, and experience. Abiologics, Inc currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Abiologics, Inc'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 privacy@flagshippioneering.com. 

Source: Flagship Pioneering, Inc. careers (Greenhouse)

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