Machine Learning Engineer

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

Employment Type: Full Time

Location: San Mateo, CA

Description

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 wetlab 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 Engineer you’ll apply your world-class ML skillset to refine and expand this state of the art protein engineering platform, and actively participate in the application of this platform to the accelerated design of new therapeutics.

Key Responsibilities

• Develop, source, and deploy generative models of antibody sequence and structure, predictive models of antibody properties, and lab-in-the-loop optimization algorithms, trained on proprietary internal datasets of thousands to millions of antibodies.
• Work with wet lab scientists to rapidly validate these tools in our weekly build-test-train loop; we only trust algorithms when they’ve successfully designed real antibodies with drug-like properties.
• Provide ML expertise and support for ongoing therapeutics programs, directly contributing to the development of new drugs.
• Collaborate with our engineering team to design, develop and deploy production-grade infrastructure for improved automated model training, tracking, benchmarking and lab validation, across diverse tasks in a continuous data generation setting.
• Work closely with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, data scientists, etc. to identify inefficiencies or potential improvements in the BigHat ML platform, and coordinate or implement solutions.

Preferred Qualifications

• BS/MS 5/3+ years of hands-on experience crafting, refining and deploying ML models in the wild.
• Strong competency in Python, familiarity with pytorch, experience deploying ML and DS stacks on AWS.
• Experience with relational databases, RESTful APIs.
• Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
• Enjoys a fast paced environment and executing across multiple projects.
• Nice-to-haves include experience with protein structure modeling and biophysics, NGS data, and familiarity with antibody biology & biophysics.