Principal Prediction & Insights Applications Engineer, Small & Large-Molecule Discovery at Bristol-Myers Squibb

San Diego, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Pharmaceuticals, BiotechnologyIndustries

Requirements

8-10 years building software or ML solutions for medicinal chemistry, biologics engineering, or high-content screening; fluent in SAR data, sequence/structure relationships, and assay lifecycles
Practical mastery of open-source and proprietary molecular-design toolkits (e.g., EvoDiff, RFdiffusion, Molformer, RDKit, Alphafold, Schrodinger, OpenEye) and ability to integrate or adapt them within proprietary pipelines
Hands-on experience fine-tuning and deploying LLMs, diffusion models, GNNs, structure-prediction models (AlphaFold family)

Responsibilities

Own the strategy and delivery of GenAI-native applications, predictive-model workflows, and insight-driven analytics platforms that accelerate small-molecule and biotherapeutic invention
Translate scientific objectives into intuitive software products and robust model-ops practices to help chemists, protein engineers, and data scientists iterate faster, uncover deeper insights, and make better decisions
Champion predictive-model use-cases across medicinal chemistry and biologics (e.g., property prediction, sequence optimization, generative design)
Harness cutting-edge structure- and sequence-prediction models (AlphaFold/OpenFold, RoseTTAFold, RFdiffusion, Schrodinger, OpenEye) to accelerate target triage, protein engineering, and binding-interface analysis
Track, evaluate, and train molecular prediction models and integrate genAI methods from literature and open-source community
Ensure model outputs, metrics, and explainability align with discovery KPIs and downstream lab workflows
Integrate agentic genAI frameworks (e.g., Bedrock, LangChain, LlamaIndex, AzureOpenAI) to create conversational analytics, automated report writers, and “copilot” agents for complex SAR, sequence, or imaging datasets
Deliver full-stack applications—React/Next.js fronts with Python/FastAPI & GraphQL services—that surface models and analytics at scale with sub-second responsiveness
Stand up automated pipelines for data curation, experiment tracking, CI/CD, and governed model release (PyTorch/TensorFlow + MLflow/Kubeflow/SageMaker + GitHub Actions)
Package and deploy predictive applications and model endpoints to cloud PaaS or on-prem containers for scalable inference and performant access
Codify reusable templates, inner-source libraries, and design systems that cut feature time-to-value by 40%
Mentor a cross-disciplinary team of full-stack and ML engineers; foster “better-than-best” practices in code quality, documentation, and UX research
Partner with discovery leads, IT operations, and external vendors to align technical backlogs with portfolio milestones and data-quality standards
Influence budgeting and make-vs-buy decisions for AI tooling and platform enhancements

Skills

GenAI

AlphaFold

OpenFold

RoseTTAFold

RFdiffusion

Schrodinger

OpenEye

ModelOps

Predictive Modeling

Property Prediction

Sequence Optimization

Protein Engineering

Bristol-Myers Squibb

Develops and delivers biopharmaceutical medicines

About Bristol-Myers Squibb

Bristol Myers Squibb (BMS) develops and delivers medicines aimed at treating serious diseases, focusing on areas like cancer, autoimmune diseases, and heart conditions. The company conducts extensive research and development to create new drugs, which are sold after receiving regulatory approval. BMS also produces generic drugs, offering affordable alternatives that meet the same quality standards as their branded counterparts. What sets BMS apart from competitors is its dual focus on both innovative and generic medicines, enhancing access to healthcare. The company's goal is to improve patient outcomes while maintaining a commitment to sustainability and corporate responsibility.

New York City, New YorkHeadquarters

1887Year Founded

$33,706.1MTotal Funding

IPOCompany Stage

Biotechnology, HealthcareIndustries

10,001+Employees

Benefits

Flexible Work Hours

Hybrid Work Options

Professional Development Budget

Risks

Increased competition in oncology from emerging biotech firms like ArsenalBio.

BMS's lawsuit over the 340B Drug Pricing Program may lead to regulatory challenges.

Rapid AI and digital tech evolution may pose integration challenges for BMS.

Differentiation

BMS focuses on innovative cancer treatments through collaborations like ArsenalBio for T cell therapies.

The company emphasizes digital health technologies, enhancing clinical trial management and patient engagement.

BMS offers both innovative and generic medicines, increasing affordable healthcare solutions.

Upsides

BMS's partnership with Medidata enhances clinical research processes and patient outcomes.

The collaboration with AI Proteins advances novel miniprotein-based therapeutics, expanding therapeutic modalities.

BMS's global license agreement with BioArctic expands its portfolio in neurodegenerative diseases.

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