Machine Learning (ML), Scientist

Machine Learning (ML), Scientist

W2 Contract

Pay Rate: $85 - $105 per hour

Location: Redwood City, CA - Remote Role

Job Summary:

We are seeking a hands-on machine learning scientist or engineer to advance drug discovery through model development or ML infrastructure. This individual contributor will own defined projects in one or more of the focus areas below, based on their expertise and project needs. Candidates should bring depth in at least one area; expertise in all three is not required.

Duties and Responsibilities:

• Fine-tuning cofolding models: Adapt and fine-tune pretrained co-folding models for protein-ligand and multiprotein complexes relevant to drug discovery. Prepare structural training data, develop reproducible training and inference workflows, and benchmark against pretrained baselines using leakage-aware splits. Evaluate structural accuracy, physical plausibility, and usefulness for discovery decisions.
• Machine learning for chemistry: Develop and evaluate models for chemistry problems such as molecular property prediction, potency, selectivity, and ADME prediction, or compound design and prioritization. Curate chemical structures and assay data, use appropriate molecular representations, and assess generalization with scaffold-based or temporal validation as appropriate.
• ML data pipelines and infrastructure: Build reliable pipelines for data ingestion, validation, transformation, and versioning. Develop reusable infrastructure for model training, experiment tracking, and batch inference. Improve workflow orchestration, automated testing, monitoring, and compute efficiency on cloud or high-performance computing systems.
• Agree on project scope, milestones, and success criteria with scientists and engineers.
• Deliver tested code, reproducible workflows, and documentation of data provenance and methods for handoff.
• Communicate findings, limitations, and progress, and incorporate feedback.

Requirements and Qualifications:

• Degree in computer science, machine learning, computational chemistry, cheminformatics, computational biology, or a related field, or equivalent practical experience.
• Strong Python skills and hands-on experience developing ML models or building data and software systems that support ML workflows.
• Experience with scientific computing or ML libraries, version control, testing, and reproducible software development.
• Ability to independently deliver defined project work, troubleshoot problems, and collaborate across scientific and technical disciplines.
• Candidates should demonstrate experience in at least one of the following focus areas:
• Cofolding models: Experience training or fine-tuning deep learning models with a framework such as PyTorch, plus familiarity with protein or protein-ligand structures. Experience with geometric deep learning, structural representations, or biomolecular modeling is relevant.
• Chemistry ML: Experience applying ML to molecular or assay data, using cheminformatics tools such as RDKit, and evaluating model performance on chemical series or compounds outside the training data.
• ML engineering: Experience building reliable data pipelines or ML infrastructure, including data validation, workflow orchestration, and cloud or high-performance computing.
• Prior drug discovery experience is helpful but not required for this focus area.

Preferred Qualifications:

• Experience in drug discovery, biotechnology, or pharmaceutical research, particularly in collaboration with experimental scientists.
• For model-focused projects, an advanced degree or equivalent research experience and familiarity with uncertainty estimation and rigorous model benchmarking are required.
• For infrastructure projects, experience with SQL, containers, distributed computing, GPU workloads, or continuous integration and deployment.

Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate.

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