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BigHat Biosciences is seeking a Director of Machine Learning to own the technical direction and hands-on execution of the company's machine learning capabilities and machine learning operations, including agent development. Reporting to the CIO, you will lead a small, senior team of ML scientists and engineers while maintaining a player-coach approach with meaningful hands-on involvement.
Key responsibilities include:
- Owning and continuously sharpening BigHat's machine learning roadmap, articulating where the field is heading and where the company intends to lead
- Developing state-of-the-art antibody property models using BigHat's unique data repository and high-throughput wet lab capabilities to demonstrate best-in-industry proof that better models accelerate real therapeutics
- Applying frontier models (including LLMs and generative models) against protein design challenges, optimizing the design loop by integrating lab, computational platform, and data with LLM automation
- Steering the unified LLM and ML approach across the CIO organization, driving adoption of safe, impactful LLMs, agent frameworks, and RL evaluation benchmarking frameworks
- Ensuring models, provenance, and benchmarks flow through infrastructure to support 2,000+ antibodies designed weekly, delivering computational deliverables to internal and partnered programs
- Translating data generation and modeling capabilities into offerings for frontier AI companies and biopharma partners; scoping pilots and defining technical success
- Mentoring and growing the ML team, setting the bar for rigor, collaboration, and intellectual honesty
- Publishing, presenting, and engaging the ML and protein engineering communities to strengthen BigHat's reputation
The role is unique in combining frontier machine learning research with an industrial-scale, purpose-built biological data platform. You will work at the intersection of AI/ML innovation and therapeutic antibody development, with direct accountability for models that differentiate therapeutic programs.
Requirements:
- Ph.D. in Machine Learning, Computer Science, Computational Biology, or related field
- 8+ years of experience developing and applying advanced ML methods (industry experience strongly preferred)
- Demonstrated leadership of technical teams or major technical programs
- Deep, current command of modern ML: generative models of protein sequence and structure, Bayesian optimization and active learning, uncertainty quantification, data-efficient predictive modeling, in-context learning
- Strong Python and PyTorch proficiency with comfort in modern software engineering practice, cloud computing, and MLOps
- Ability to reason from first principles about why methods should work, design falsifiable experiments, and explain concepts clearly to interdisciplinary audiences
- Player-coach instinct: lead by doing as well as by directing; energized by writing code and running benchmarks alongside your team
- Shipped ML into production systems with demonstrated care for reproducibility, provenance, benchmarking, and cycle time
- Working knowledge of antibody biology, developability, and drug development, or demonstrated ability and appetite to acquire it quickly
- Familiarity with display, NGS, and high-throughput biophysical data is a strong plus
- Excellent written and verbal communication; thrive in interdisciplinary settings
- Motivated by BigHat's mission to bring safer, more effective antibody therapies to patients
