Machine Learning Engineer DS

1 month ago

San Mateo, United States BigHat Biosciences Full time
The Role: We are seeking a self-motivated, experienced Machine Learning Engineer* to develop, deploy, and refine tools to accelerate our antibody design cycle.
*At BigHat we believe in titles that are commensurate with skill set, relative organizational impact, and value contribution; more experienced candidates are encouraged to apply, with the understanding that responsibilities and title would adjust as appropriate.
At BigHat Biosciences, our machine learning stack is tightly integrated with a high-throughput wet lab to rapidly design, validate, and iteratively refine the first generation of ML-engineered antibody therapeutics. Our bespoke platform channels data from automated lab instruments to data processing pipelines, custom validation and QC, ML data ingestion ETLs, and finally, through predictive ML models and sequence optimization algorithms which produce the next set of antibody designs, ideally one step closer to a beneficial therapeutic but always generating valuable training data.
You’re not interested in any model thrown at any data. Motivated by an enthusiasm for the possibility of addressing unmet patient need, and a curiosity about the underlying biology, as an ML Engineeryou’ll apply your world-class ML skillset to refine and expand this state-of-the-art protein engineering platform, improving the effectiveness with which it can be used to design new therapeutics. Job Responsibilities
  • Rapidly implement, evaluate and deploy predictive machine learning models of diverse antibody biophysical properties, for dataset scales from hundreds to millions, to support BigHat’s therapeutic portfolio.
  • Design and develop production-grade infrastructure for better model training, tracking, benchmarking and lab validation, across diverse tasks in a continuous data generation setting. 
  • Accelerate our multiobjective antibody optimization programs by developing, identifying or refining data- and domain-appropriate ML-driven protein sequence design tools.
  • Work closely with ML and DS team members to identify inefficiencies or potential improvements and coordinate or implement solutions.
  • Provide support for ongoing ML-guided antibody engineering therapeutics programs at BigHat.
  • Collaborate closely with BigHat engineering, data science, and lab teams to ensure ML tooling is tailored to our experimental platform and therapeutic development goals.

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