10 months ago
Base Salary
$190k - $260k/yr
Responsibilities
- Own end-to-end applied research from problem framing and experiment design through production deployment and real-world impact monitoring
- Set technical direction across LLMs, retrieval, and multimodal modeling and conduct ablations and error analyses that influence product decisions
- Build evaluations connecting offline metrics to online outcomes and define thresholds, monitoring, and rollback procedures
- Partner with engineering, product, clinicians, and domain experts to align data, success criteria, and timelines
- Mentor peers and establish standards for reliability, safety, and documentation
- Improve data, training, serving, and observability platforms to accelerate iteration and reproducibility
- Explore strategic computer vision and vision-language research directions
Requirements
- MS or PhD, or equivalent research experience, in Computer Science, Electrical Engineering, Computational Linguistics, Biomedical Informatics, or a related quantitative field
- At least 7 years of applied ML research experience, or a PhD plus 5 years, or equivalent evidence of Staff-level impact
- Depth in one or more of LLMs and NLP, computer vision, speech, recommendation/ranking, retrieval, or multimodal modeling
- Strong experimental rigor, including hypothesis framing, offline-to-online linkage, calibration, stratified analyses, and decision-influencing ablations
- Proven ability to take models into production
- Hands-on experience with PyTorch and modern experiment or operations tools such as MLflow, Databricks, Ray, or similar
- Ability to design for observability and rollback and clearly document technical decisions
- Strong written and verbal communication skills, including design documentation and explaining complex ideas to non-specialists
- Experience with health data such as EHR or imaging is preferred
- Experience with clinical NLP or LLMs, computer vision, speech, retrieval, or multimodal modeling is preferred
- Experience shipping and measuring monitored production models, with external or multi-site validation a plus
- Experience integrating workflows with EHR, RIS, PACS, or reporting systems is preferred; PowerScribe or Dragon exposure is helpful
- Experience with safety and governance in sensitive domains, including PHI handling and HIPAA- or FDA-adjacent environments, is preferred
- Technical mentorship, research-culture contributions, publications, or impactful open-source work are preferred
- Experience with PyTorch and ML operations tools such as MLflow, Databricks, Ray, or Triton is preferred
Benefits
- Comprehensive medical, dental, vision, and life insurance
- HSA with employer match, FSA, and DCFSA
- 401(k)
- 11 paid company holidays
- Flexible PTO policy
- Annual company-wide offsite and periodic team offsites
- Annual equipment stipend
- Applicants may work across the United States, with a preference for the role to be based in the San Francisco office
Tech Stack
Categories
AI ResearchML Engineering
About Rad AI
Our mission is to empower physicians with Al - saving physicians time, reducing burnout, and improving the quality of patient care.