Senior Director / Vice President, Machine Learning (Generative Chemistry)

Description

The company is a venture-backed, still-stealth startup that combines AI and biology. It is hiring a Senior Director or Vice President of Machine Learning for Generative Chemistry.

You will lead AI/ML and cheminformatics work on next-generation multi-modal generative models for designing biomolecules. You will set a practical AI strategy and guide method and platform work, including systems design, drug design, molecular modeling, and LLM or agent-based workflows. You will also make sure model development, benchmarking, and scaling are done rigorously.

You will manage a computational group that spans AI/ML, molecular simulation, and cheminformatics, and your input will shape how the company is built.

The role suits independent leaders who enjoy ambitious work in a quick-moving setting and want to advance AI-driven drug discovery.

Responsibilities

• Lead several AI/ML or computational projects within assigned ventures, covering development, execution, oversight, and reporting, in line with broader strategy, budgets, and timelines.
• Take a hands-on technical role on project teams, guiding method and pipeline development and the design of LLM-based agents and workflows.
• Push benchmarking and scaling work and turn promising results into production-grade systems.
• Lead and coordinate scientists, engineers, and cross-functional project teams, mentor early hires, and help with recruiting and interviews.
• Help plan projects, including budgets, staffing, and timelines, and raise risks and tradeoffs early with clear options.
• Independently track new literature and the AI/ML field, and turn what you find into development strategies and opportunities for ventures and the wider portfolio.
• Build good engineering habits across AI projects by teaching cross-functional colleagues.

Requirements

• Master's or PhD in computer science, AI/ML, physics, biophysics, or a related field.
• 7+ years in scientific, engineering, or computational roles in pharma or biotech.
• Experience getting results through teams of engineers and scientists, directly or through others, in dynamic, entrepreneurial, technical settings.
• Clear record of independent, creative thinking that produced high-impact work in drug development and chemistry AI/ML.
• Track record of leading, and influencing decisions on, advancing AI/ML models within projects or programs.
• Working depth in Python, modern ML frameworks (PyTorch or JAX/TensorFlow), version control, databases, deep learning architectures, and informatics software.
• Consistently strong output, shown through publications, patents, or high-impact internal reports where relevant.
• Demonstrated ability to lead technical initiatives, report progress clearly, and drive innovation in generative biomolecular design.
• Preferred: industry AI/ML experience.
• Preferred: breadth across protein modeling and design, cheminformatics, docking, ADMET, biophysics, molecular dynamics, and LLM or agent-based automation.
• Preferred: a strong presence in the ML community through publications and conference papers.
• Preferred: MLOps skills, including data versioning and lineage (such as DVC or LakeFS), experiment tracking (MLflow or W&B), AWS infrastructure (S3, Batch, ECS, EKS, SageMaker), Docker, infrastructure as code (Terraform or CDK), and CI/CD (GitHub Actions).
• Preferred: generative modeling with diffusion, flow, or VAE methods for sequences, graphs, or 3D structures, and docking rescoring with pose quality metrics (such as gnina or DiffDock).
• Preferred: workflow orchestration (Airflow, Prefect, or Argo), data warehouses (Redshift or Snowflake), vector search (FAISS or pgvector), and lightweight internal tools (FastAPI or Streamlit/Gradio).
• Preferred: ML software development and cloud services, such as Docker, AWS Batch, Step Functions, EKS, and AWS ParallelCluster.
• Preferred: scientific libraries such as RDKit, Rosetta, ProDy, Biopython, PyMOL, OpenMM, Dagster, and Prefect.
• Preferred: experience mentoring early hires, serving as interim Head of ML, and shaping hiring plans and interviews at startups.

Conditions

The salary range is $279,000 to $412,500. Actual pay depends on factors such as qualifications, skills, competencies, and experience.

Pay and benefits figures are the company's good-faith estimate at the time of posting and may change later.

The company welcomes applicants who meet some but not all of the listed criteria and is committed to building diverse, inclusive teams.

Benefits

• Healthcare coverage.
• Annual incentive program.
• Retirement benefits.
• A broad range of other benefits.