Senior / Staff Research Engineer - Data Science and ML

Key Skills

CUDA/GPU programming, Data science techniques, Design, Drug Discovery, Large Language Models - LLMs, Machine learning techniques, Python Programming

Job Description

The Opportunity

insitro’s approach to rethinking drug development applies innovative data science and machine learning, at scale, throughout the discovery process. As a Research Engineer, you will help implement, validate, and deploy our largest and most complex methods and models. We work on a variety of problem domains and datasets, including multi-petabyte collections of high-content biological imaging, genomics, and biomolecular structures. To support insitro’s work at this scale, our team is passionate about the craft of scientific software engineering, ensuring that our tools, infrastructure, and models are scalable, correct, maintainable, and robust. You will work closely with our data scientists, software engineers, biologists, and laboratory scientists to find opportunities and implement projects that will aid our drug discovery efforts. Typical projects might include onboarding methods from research papers, reducing the cost of training existing models, crafting a framework for benchmarking competing methods, or working alongside scientists to deploy methods at scale. While not required, some knowledge of biological or chemical data is valuable in understanding the unique requirements and applications of ML to biology and drug discovery.

About You

• Ph.D. in computer science, statistics, mathematics, physics, engineering, plus two years additional experience, or equivalent experience (for example, BS plus 7 years experience)
• Research experience with modern data science techniques; machine learning experience is required, but expertise in other techniques may also be helpful, such as Bayesian inference or probabilistic programming
• Fluency in one or more general-purpose programming languages (strong preference for experience in scientific Python)
• Experience working with teams throughout the full lifecycle of designing, implementing, deploying, and maintaining robust scientific software
• Strong desire to deliver work that aids in pioneering drug discovery!

Nice to Have

• Experience building, shipping, and benchmarking large-scale ML systems, foundation models, or large language models (LLMs)
• Experience with data modalities relevant to drug discovery, such as microscopy, genetics, or natural language, including patient records, and scientific literature.
• Experience working on ML experimentation tooling and platforms
• Experience working with high-performance computing resources, such as GPU clusters
• Past experience working on multi-functional teams
• Previous open-source contributions or publications demonstrating impact in relevant projects

Compensation & Benefits at insitro

Our target starting salary for successful US-based applicants for this role is $185,000 - $225,600. To determine starting pay, we consider multiple job-related factors including a candidate’s skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data. 

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.

In addition, insitro also provides our employees:

• 401(k) plan with employer matching for contributions
• Excellent medical, dental, and vision coverage (insitro pays 100% of premiums for employees), as well as mental health and well-being support
• Open, flexible vacation policy
• Paid parental leave
• Quarterly budget for books and online courses for self-development
• Support to occasionally attend professional conferences that are meaningful to your career growth and development
• New hire stipend for home office setup
• Monthly cell phone & internet stipend
• Access to free onsite baristas and cafe with daily lunch and breakfast
• Access to free onsite fitness center
• Commuter benefits