Senior / Staff Research Engineer - LLM Tools
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. We are looking for an experienced engineer to help us harness the potential of recent improvements in large language models (LLMs) throughout the drug discovery process. You will work closely with our data scientists, software engineers, biologists, and laboratory scientists to identify, build, and deploy innovative internal tools and products based on LLMs. Potential projects might include providing natural-language data analytics to our scientists, querying scientific literature, or building co-pilots specialized to our ecosystem. 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.
- M.S. in computer science, statistics, mathematics, physics, engineering, plus five years additional experience, or equivalent experience (for example, BS plus 7 years experience)
- Experience working with applications of LLMs or other natural-language systems
- 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 software, including deploying at least one real-world ML system
- Strong desire to deliver work that aids in pioneering drug discovery!
Nice to Have
- Experience training, 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
insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process.