Machine Learning Scientist — Large Multimodal Models (Post-Training)
Posted
Tech Stack
Responsibilities
- Research and develop post-training strategies for large-scale multimodal foundation models
- Design reward functions, training objectives, data-generation strategies, and evaluation protocols for reinforcement learning
- Build systematic experimentation and hyperparameter optimization workflows to explore post-training recipes
- Develop and apply inference optimization techniques to support deployment in high-throughput workflows
- Design and maintain rigorous benchmarking and evaluation frameworks that measure model quality across modalities
Benefits
- 401k
- Gym Membership
- Health Insurance
- Remote Work
Culture
Cross-Functional TeamsMission-DrivenInclusive Hiring
Requirements
Required: PhD in machine learning, computer science, computational chemistry, physics, or a related computational STEM field, or equivalent industry experience demonstrating comparable depth
Regions: Us
Get jobs like this in your inbox
Weekly Docker, Kubernetes, Python hiring trends and salary data — free.
Join 8 engineers getting weekly insights
Get job market intelligence in your inbox
Free weekly insights on tech hiring trends, salaries, and in-demand stacks.
Already a subscriber? Sign in
About iambic-therapeutics
Industry: healthtech
Size: small
Iambic Therapeutics is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform.
View company profile →Similar Jobs
Machine Learning Scientist – Clinical Prediction
iambic-therapeutics · Boston Office
Member of Technical Staff
latentlabs · San Francisco
Research Scientist
latent · San Francisco
$225k
Machine Learning Scientist (All Levels)
abridge · SF Office
(Senior) ML Scientist
insitro · South San Francisco, CA
$183k – $238k