Principal Machine Learning Scientist

🕒 August 5

🏄 California – Remote

🏄 California – Remote

💵 $254k - $290k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

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BigHat Biosciences

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

🏥 Healthcare

💼 Consulting

🏭 Manufacturing

Healthcare • Consulting • Manufacturing

BigHat Biosciences is a biotechnology company focused on designing safer, more effective antibody therapies using machine learning and synthetic biology. The company leverages its Milliner platform, which integrates a high-speed wet lab with state-of-the-art machine learning technologies, to discover and engineer antibodies for intractable diseases like infections and cancers. Their approach promises to deliver next-generation therapies with improved safety and efficacy. Based outside San Francisco, BigHat Biosciences engages in strategic collaborations and partnerships to enhance their therapeutic programs and has raised significant funding to pursue these innovative solutions.

📋 Description

• Design and implement generative models of antibody sequence and structure, and predictive models of antibody properties • Provide leadership, technical guidance, and mentorship to ML and data science employees and interns • Help set strategy for future ML research based on BigHat programs, operations, and drug development challenges • Develop and deploy de novo design methods for generating initial hits to therapeutically interesting targets • Develop multi-modality, multi-objective iterative protein sequence optimization for lab-in-the-loop antibody design • Maintain an in-depth understanding of ML-driven protein engineering • Share findings at top-tier conferences and publish in leading scientific journals • Provide ML expertise for therapeutics programs and contribute to new drug development • Collaborate with engineering on automated and agentic deployment of models • Work with interdisciplinary drug development, wet lab, automation, and data science teams to identify platform improvements and prioritize ML methods development

🎯 Requirements

• PhD in ML/CS or hard sciences with 5+ years of post-graduation experience developing and applying novel ML methods • Strong quantitative background • Publications in major ML conferences and/or leading journals • Extensive demonstrable track record developing and applying novel ML in industry • Strong competency in Python • Familiarity with PyTorch • Experience with modern software engineering best practices • Excellent communication skills • Sufficient biomedical domain knowledge to interact effectively with diverse scientific teams • Ability to execute across multiple projects in a fast-paced environment • Familiarity with the current state of the art in ML-driven protein engineering • Nice-to-haves: experience with de novo design, NGS data, Bayesian optimization, antibody biology and drug development, and training and deploying models on AWS

🏖️ Benefits

• Range of health insurance plan options through Anthem and Kaiser (monthly credit if benefit waived) • Dental, and vision coverage through Guardian • Additional well-being benefits through Nayya, OneMedical, Wagmo, Rula, and more • 401(k) with company match • DTO, two weeks of company-wide shutdown, and 12 company holidays • Paid parental leave • Bonus • Options