Latent
Research Scientist
San Francisco · Staff+
Sponsorship not specified$225k-$300kDetected 99 days ago
Machine LearningDeep LearningPyTorchNLPLLMsPatient CareResearchExperimental Design
About the role
- We are primarily hiring for senior and staff-level engineers who are comfortable owning critical research problems end-to-end.
- This role involves working on problems that directly impact real patient outcomes.
Responsibilities
- Own research initiatives end-to-end, including problem formulation, experimental design, modeling, and evaluation
- Develop novel architectures, training methods, and objectives leveraging longitudinal patient data
- Design rigorous evaluation methodologies to assess model reasoning, correctness, and clinical relevance
- Make and own tradeoffs between model capability, interpretability, and verifiability in high-stakes settings
- Collaborate with clinicians and engineers to define meaningful problem formulations grounded in real-world workflows
- Partner with ML engineers to ensure research translates into deployable systems
Requirements
- Track record of driving ML research or novel modeling work from idea to validated results
- Experience working on ambiguous research problems with limited prior art
- Hands-on experience with PyTorch or similar frameworks
- Ability to operate independently in high-ambiguity environments with minimal guidance
- Comfort working in a fast-moving, early-stage environment
Nice to have
- Publications at top-tier ML venues (e.g., NeurIPS, ICML, ICLR)
- Experience with LLMs, NLP, or sequence modeling
- Experience working with longitudinal or structured data at scale
- Experience working with clinical, biomedical, or scientific domains
- Work on high-stakes problems with real impact on patient care
- Significant ownership in a small, high-caliber team
- We spend most of the week in the office and prioritize candidates who are excited to work this way.
Skills
- those with wealth and access, and those with physicians in their immediate family.
- For everyone else, care is fragmented and impersonal.
- Medical history is scattered across systems that don't communicate.
- Physicians have minutes to understand decades of context.
- And when something goes wrong, patients are left with tools that understand medicine broadly-but not the individual.
Compensation
- Base salary: $225,000 - $300,000+
Benefits
- Work on verifiable reinforcement learning, mid-training, and post-training of foundation models
- Strong foundation in machine learning, deep learning, or a related technical field
- As a Machine Learning Engineer, Research, you will own the design and development of novel modeling approaches that advance state-of-the-art clinical intelligence.
- Meaningful equity in an early-stage, Series A company
- If you're interested in building systems that bring truly personalized healthcare to millions of patients, we'd love to talk.
Company info
- Verifiable reinforcement learning at scale
- Mid-training and post-training of foundation models
- Novel objectives derived from longitudinal patient data
This listing is sourced directly from Latent's careers page and normalized into a canonical job model.