(Senior) ML Scientist

The Opportunity

Key to insitro’s approach to rethinking drug development is leveraging disease models, genetics, and clinical datasets to link in vitro and cellular phenotypes with patient outcomes. Machine Learning for science plays a key role across the value chain in Insitro’s approach towards data driven drug discovery. As a machine learning scientist, you will develop cutting edge ML approaches to analyze and integrate large-scale biological, human, or chemical datasets.

You will work with colleagues across different domains of ML and contribute models, methods, algorithms, analysis techniques, and code towards improving the Insitro platform in concrete, measurable ways and to push the field forwards with IP and publications. You will develop techniques and infrastructure for relevant problems in the drug discovery setting inspired by Insitro’s needs under various real world conditions, such as distribution shift, data missingness, causal inference, small sample sizes, decision making, and many other problems.

You will also work closely with a cross-functional team of life scientists, statistical geneticists, bioengineers, computer vision scientists, genomics scientists, medical scientists, and software engineers to integrate human-level data with our high-throughput in-house in vitro genomic and phenotypic data, with the goal of identifying therapeutic targets and developing drugs that have high efficacy and low toxicity.

You will be joining a vibrant biotech startup that has long-term stability, due to significant funding, and is in a high growth phase. A lot can change in this early and exciting phase, providing many opportunities for significant impact. You will work closely with a very 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!

This role is preferably based in the San Francisco Bay Area but we are open to candidates based anywhere in the US; we will also consider candidates from non-US locations on a case-by-case basis.

About You

• Ph.D. in machine learning, computer science, or a related discipline, or equivalent practical experience (e.g., a Masters degree plus 2 years in relevant industry experience)
• Demonstrated ability to use and develop cutting edge statistical and machine learning methods inspired by real problems
• Experience in modern representation learning topics such as self-supervised learning, transfer learning, multi-modal modeling, few-shot learning, robustness and interpretability, uncertainty estimation, and more
• Experience in probabilistic modeling and/or causal inference
• Experience using modern deep learning frameworks (PyTorch, Jax, etc)
• Proficiency in Python
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Passion for making a difference in the world.

Nice to Have

• Publication record in venues such as NeurIPS, ICML, ICLR, AISTATS, AAAI, and related
• conferences/journals in the sciences
• Hands-on experience working with biomedical or other real world datasets
• Experience with probabilistic programming
• Familiarity with cloud computing services (e.g., AWS or GCP)
• Proficiency in scientific engineering and modern engineering practices

Compensation & Benefits at insitro