Senior Machine Learning Scientist, Imaging
Posted
$215,000 – $235,000 USD
Tech Stack
Responsibilities
- Partner with experimental and computational biologists to design, troubleshoot, and optimize high-throughput imaging-based experiments and workflows
- Identify, understand, develop, and deploy novel computer vision and machine learning methods such as segmentation, feature extraction, and representation learning to extract features from microscopy image datasets
- Work closely with software engineers to build robust and well-tested image analysis workflows, able to be used by experimental and computational biologists with minimal direct support
- Calibrate analysis tools and workflows, define performance metrics, and conduct benchmarking to select fit-for-purpose solutions
- Communicate findings to cross-functional stakeholders through reports, visualizations, presentations, and publications
Benefits
- 401k
- Equity
- Health Insurance
- Learning Budget
- Parental Leave
- Remote Stipend
Culture
Cross-Functional TeamsGrowthWork-Life BalanceInclusive HiringMentorship Program
Requirements
Required: Ph.D. in computer vision, machine learning, computer science or a related discipline, or a Master's degree and 2+ years of relevant industry experience
Regions: Us
Get jobs like this in your inbox
Weekly AWS, Azure, Python hiring trends and salary data — free.
Join 6 engineers getting weekly insights
Get market intelligence in your inbox
Free weekly insights on tech hiring trends, salaries, and in-demand stacks.
Already a subscriber? Sign in
About insitro
Industry: biotech
Size: small
insitro is a drug discovery and development company that uses machine learning and data at scale to decode biology for transformative medicines, leveraging in-house generated multi-modal cellular data and high-content phenotypic human cohort data to develop predictive disease models.
View company profile →Compensation
Base salary: $215,000 – $235,000 USD
Equity: Eligible for Equity Incentive Plan
Bonus: Annual Performance Bonus Plan (based on company targets by role level and annual company performance)