Director of Machine Learning

Department: DS/ML (Data Science/Machine Learning)

Employment Type: Full Time

Location: San Mateo, CA

Reporting To: Eddie Abrams

Compensation: $250,000 - $365,000 / year

Big Hat Biosciences is seeking an exceptional player-coach to serve as Director of Machine Learning. Reporting to the CIO, you will own the technical direction, and a meaningful share of the hands-on execution, of Big Hat's machine learning capabilities and the growing domain of machine learning operations, including agent development and how agents automate and extend our internally built computational platform and force multiply the impact of our teams.

We are looking for someone with genuine theoretical depth and the vision to say where ML-driven antibody design should go next. Your team will develop state-of-the-art antibody property models with the goal of iteratively improving our antibody designs and you’ll own the proof points that demonstrate the impact of these models. You’ll build agent services to bolster the agility and impact of our teams and work with frontier AI labs to adapt LLMs to new agentic antibody design challenges.

As our platform value grows, so does our opportunity to create new and valuable platform partnerships. You will be accountable for the ML that differentiates our therapeutic programs, and for the modeling capabilities we put in front of data and model partners.

At Big Hat, we only declare success upon synthesis of real antibodies with drug-like properties that improve patient outcomes. This is a rare opportunity to run frontier ML within a one-of-a-kind production platform, with an automated high-throughput wet lab generating the data to fuel it.

• ML strategy and vision: Own and continuously sharpen Big Hat's machine learning roadmap. Articulate where the field is going and where we intend to lead.
• Deliver best in class therapeutic models: Utilize Big Hat’s data repository and data generation capabilities to create multi-objective predictive models to demonstrate a durable, benchmarked, best-in-industry proof that better models accelerate real therapeutics. Develop and train models that support the safe and effective creation of increasingly sophisticated, multi-specific antibodies that patients need today.
• Frontier models joined with best-in-class data
  :
  Apply frontier models, utilizing Big Hat’s unique datasets and data capabilities, against nature’s hardest protein design challenges. Optimize our design loop by integrating our lab, computational platform and data with LLM automation.
• Agentic direction
  :
  Join forces across the CIO organization to steer our unified LLM and ML approach. Relentlessly drive our adoption of safe, impactful LLMs and similar models, agent frameworks and RL evaluation benchmarking frameworks to empower every Big Hatter.
• Program impact: Ensure that models, provenance, and benchmarks flow through our infrastructure without heroics, and that build-test-train design rounds fully leverage model insight for all 2k+ antibodies designed each week. Be accountable for computational deliverables to internal and partnered programs, delivering timely analyses, predictions, and optimized variant sets that drive progress toward clinic-ready molecules.
• Platform as product: Work with business development, partnerships, and executive leadership to translate our data generation and modeling capabilities into offerings that frontier AI companies and biopharma partners can buy. Scope pilots, define what technical success looks like, and deliver it.
• Team leadership: Mentor and grow a small, senior team of ML scientists and engineers. Set the bar for rigor, collaboration, and intellectual honesty, and create the conditions for people…