(Senior) ML Scientist

(Senior) ML Scientist

insitro is a data-driven drug discovery and development company that leverages machine learning and high-throughput biology to transform the way medicines are created to help patients.

The Opportunity

State-of-the-art technologies that measure multiple cellular aspects of in-vitro biology are at the heart of insitro's efforts to accelerate drug development. Computational biology is key to elucidating the relationship between these phenotypes and human disease and translating them into actionable outcomes.

We are looking for an expert in ML method development for biological data analysis, in domains such as network analysis, systems biology, graph-based modeling, causal structure learning, single cell omics, or imaging modalities. Your expertise will help the team navigate the complexities of developing disease relevant cell models and analyzing high throughput phenotypic screens, and ensuring that the tools being developed are calibrated and effective, and that analyses are performed to the highest rigor and in line with best practices in the broader scientific community.

In this role, you will collaborate closely with experimental biologists, computational biologists, and other machine learning scientists, support the identification of novel phenotypes, the development of new screening paradigms, and advance our understanding of disease. You will develop and utilize diverse machine learning and bioinformatic methods to perform diverse downstream analyses, including integrating with other data modalities, including human cohort data in order to extract insights about disease mechanisms. You will be part of a cross-functional team of life scientists, data scientists, bioengineers, software engineers, and machine learning scientists that strive to identify therapeutic targets and develop drugs of high efficacy and low toxicity. This role will be reporting to the Head of Computational Biology and ML-Omics. This is a hybrid position that requires you to be in our South San Francisco headquarters at least three days per week.

You will be joining a vibrant biotech startup that has many opportunities for significant impact. You will work closely with a highly talented team, learn a broad range of skills, and help shape insitro's culture, strategic direction, and outcomes. Join us, and help make a difference to patients!

About You

• Ph.D. in computer science, machine learning, computational biology, systems biology, or a related discipline.
• Extensive hands on experience developing ML methods for biological data modalities
• Hands on experience with biological data analysis, in particular familiarity with network and graph based analysis and modeling techniques
• Experience integrating data or insights from multiple sources and distinct modalities (e.g., imaging, transcriptomics, functional genomics, genetics, human cohort data)
• Strong programming skills in scientific programming languages (i.e., Python)
• Committed to writing well-commented code and documentation, and familiarity with coding best practices (i.e. version control, code review)
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Publication record of meaningful contributions to high-quality work in relevant machine learning, computational biology, systems biology, life sciences, or biomedical venues
• Passion for developing useful and impactful methods and making a difference in the world

Nice to Have

• Experience with statistical genetics and integrating functional and omics data with gwas
• First-hand experience studying disease biology
• Passionate about problem solving, asking questions and learning independently
• Experience with gene regulatory network inference or causal modeling
• Familiarity with cloud computing services (e.g., AWS or azure)
• Demonstrated ability to write software in a team, industry experience or substantial involvement with open source projects
• Experience building infrastructure for data processing

Compensation & Benefits at insitro

Our target starting salary for successful US-based applicants for this role is $183,000 - $238,000. 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 as well as mental health and well-being support
• Open, flexible vacation policy
• Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)
• Quarterly budget for books and online courses for self-development
• Support to attend professional conferences that are meaningful to your career growth and role's responsibilities
• New hire stipend for home office setup
• Monthly cell phone & internet stipend
• Access to free onsite baristas and daily lunch for employees who are either onsite or hybrid
• Access to a free commuter bus network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area

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.