(Senior) Director, Imaging Machine Learning
Insitro
Software Engineering
San Francisco, CA, USA
Posted on Monday, April 24, 2023
The Opportunity
The ability to extract biologically and clinically meaningful signals from high content imaging data is at the heart of insitro’s efforts to rethink drug development. We develop and apply advanced machine learning methods both to microscopy data produced in our in-house lab and to imaging data from human clinical cohorts to construct disease-relevant phenotypes and to identify causal factors for those phenotypes, which help reveal new therapeutic interventions.
As Head of Imaging you will lead the insitro imaging team within the Machine learning org on its mission to analyze insitro’s image-based datasets, develop cutting edge CV approaches to serve our needs, and contribute engineering artifacts to insitro’s ML platform. You will coordinate a team that develops infrastructure and machine-learning techniques to process both cellular in vitro data and patient medical images, in order to further insitro’s mission. 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.
In this role, you will:
- Lead and grow a team of outstanding machine learning imaging scientists
- Guide your team to develop and deploy ML to analyze data from diverse imaging modalities, ranging from fixed and live cell microscopy to histopathology to MRI
- Onboard and build on state of the art computer vision methods, while also bringing in an understanding of the unique needs of biomedical imaging modalities
- Lead yearly and quarterly planning, set impactful goals, and align with with cross-functional stakeholders
- Engineer robust, reusable platform components in partnership with the software engineering team
- Work with biologists and automation engineers to design experiments that generate datasets that are fit for purpose for machine learning, including ones generated explicitly for training ML models
- Work with the corporate development and strategy teams to acquire relevant external data sets
- Collaborate with colleagues working on complementary data modalities (‘omics, clinical annotations, etc) to help produce a holistic, multimodal view on human disease stat
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 or Boston, but we are open to discussing other locations in the United States and the UK.
About You
- Ph.D. in machine learning, computer vision, computer science, or a related discipline, or equivalent practical experience
- 5+ years experience working in industry and managing projects and deliverables
- Experience and demonstrated ability to build and lead teams of engineers and scientists, including recruiting and mentoring team members
- Demonstrated ability to architect and build reusable code infrastructure and work with engineering teams
- Demonstrated ability to use and develop cutting edge computer vision methods inspired by real problems
- Demonstrated ability to work with and analyze medical imaging data (e.g., histopathology), cell imaging data, or ideally both
- 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 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 high profile venues in machine learning, computer vision, or life sciences
- High profile venues in machine learning, computer vision, or life sciences
- Familiarity with cloud computing services (e.g., AWS or GCP)
- Exposure to basic concepts in biology or medicine
- Proficiency in scientific engineering and modern engineering practice
Compensation & Benefits at insitro
Our target starting salary for successful US-based applicants for this role is $235,000 - $300,000. To determine starting pay, we consider multiple job-related factors including a candidate’s skills, education and experience, the level at which they are actually hired, 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
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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.