Senior Manager / Director, Small Molecules Machine Learning

Insitro's mission is to bring better drugs faster to the patients who can benefit most, through machine learning and data at scale. A key part of that mission is to rapidly identify safe and effective molecules that modulate novel targets that emerge from our biology discovery engine. Towards that goal, we have been building a cutting-edge, machine-learning-enabled capability to design and optimize small molecule therapeutics. Our work is enabled by proprietary experimental capabilities, including: generation of extensive binding, selectivity and affinity data via our second generation DNA-encoded library (DEL) platform; rapid synthesis to assay; ML-enabled measurement and analysis of high-content cellular phenotypes driven by small molecule perturbations; and the enablement of active learning via internal lab capabilities and extensive automation. In this role, you will collaborate with our world-class teams in drug discovery, software engineering, lab automation, and cell biology to build a unique approach for rapidly designing and optimizing small molecule therapeutics that have high efficacy, low toxicity and excellent pharmaceutical properties.

In this role, you will:

• Work collaborative with our Drug Discovery leaders on the strategy for deployment of advanced ML to accelerate and optimize small molecule drug discovery

• Lead and grow a team of outstanding machine learning scientists

• Guide your team to develop and deploy ML methods to analyze data from diverse small molecule data sets, including DEL binding data, pharmacological properties, and high-content functional readouts

• Onboard and develop ML-based molecular design methods, spanning from large data regimes (e.g., from DELs) to low-data regimes (few-shot or zero-shot), and including both predictive models and generative models

• Lead yearly and quarterly planning, set impactful goals, and align with cross-functional stakeholders

• Engineer robust, reusable platform components in partnership with the software engineering team

• Work with our chemistry and automation teams to design experiments that generate datasets that are fit for purpose for machine learning, including ones generated explicitly for training ML models

• Collaborate with the corporate development and strategy teams to assess potential external partners for molecular design collaboration and to acquire external data sets

You will be joining an exciting tech bio startup that has long-term stability due to significant funding, but that is still very much in formation. You will have ample opportunities for growth and impact. You will work closely with a diverse and 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, chemistry, biochemistry, or a related discipline, or equivalent practical experience (e.g., a Masters degree plus 2 years in relevant industry experience)

• At least 5 years of industry experience in the field, including at least 2 in a line management or technical leadership role

• Peer reviewed publications in high-quality conferences or journals

• Demonstrated in-depth knowledge in the foundations and practice of modern machine learning, including deep learning, and their application to diverse molecular design tasks ● Considerable experience working with machine learning methods for small molecule chemistry across diverse tasks

• Demonstrated ability to lead a team of scientists and engineers to plan, execute and deliver a full machine learning solution for challenging, real-world problems: sourcing and qualifying training data; designing and implementing machine learning models; testing & benchmarking; shipping stable, robust, high-performance code.

• Extensive experience developing models using modern deep learning frameworks (PyTorch, TensorFlow, Keras, etc)

• Demonstrated ability in software engineering, including expertise in one or more general-purpose programming languages (such as Python, Java, Scala, C/C++, or Go) and experience with cloud computing (preferably AWS)

• Proven ability to mentor, coach, and lead junior scientists

• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions

• Passion for providing better medicine to patients in need

Nice to have

• Experience working on real world drug discovery campaigns

• Familiarity with non-ML methods for molecular design, such as traditional cheminformatics and molecular dynamics

• Exposure to ML methods in a low-data regime (few-shot or zero-shot learning)

Compensation & Benefits at insitro

Our target starting salary for successful US-based applicants for this role is $215,000 - $265,000. 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 (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

About insitro

insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro's approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience, oncology and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com.