Level

Latent

Research Scientist

Latent is hiring a Research Scientist in San Francisco, United States. It pays $225k-$300k a year and Level rates it ; you can apply on Latent.

Level's read on this job

  • Level rates this research scientist role Builds AI ●●●●: the job is building AI systems.
  • Pay on this posting starts 18% higher than the typical research scientist posting on Level.
  • The posting mentions PyTorch and NLP among its tools and skills.
  • Latent has 24 other open roles on Level.

AI in this role

pytorch
nlp

About Latent

Latent is the enterprise pharmacy intelligence platform, powered by a clinical agentic engine, that enables health systems to grow their pharmacy operations and serve more patients. One engine works across the pharmacy journey to identify patients who qualify for care, improve medication access, capture eligible prescriptions and support patients throughout treatment. Latent’s platform enables more than 60 leading health systems that collectively serve an estimated 70 million people. Founded by Sriram “Sri” Somasundaram and Rishabh Jain, Latent has raised $80 million from Transformation Capital, Spark Capital, Conviction, General Catalyst, Y Combinator, and others.

The Role

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.

You will drive research from ambiguous problem definition through to validated results and downstream impact, shaping the technical direction of how models learn from longitudinal patient data.

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.

What You’ll Do

  • 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

  • Work on verifiable reinforcement learning, mid-training, and post-training of foundation models

  • 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

What We’re Looking For

  • Strong foundation in machine learning, deep learning, or a related technical field

  • 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

  • Strong technical judgment — you can identify meaningful problems, design appropriate approaches, and evaluate results rigorously

  • Comfort working in a fast-moving, early-stage environment

  • Experience working on systems where decisions have real-world consequences (e.g., healthcare, finance, infrastructure)

Nice to Have

  • Publications at top-tier ML venues (e.g., NeurIPS, ICML, ICLR)

  • Experience with LLMs, NLP, or sequence modeling

  • Experience with reinforcement learning or alignment methods

  • Experience working with longitudinal or structured data at scale

  • Experience working with clinical, biomedical, or scientific domains

Why Join Latent

  • Backed by top-tier investors including General Catalyst, Conviction, and Y Combinator

  • Work alongside a high-caliber team building products our healthcare partners love

  • Work on mission-critical problems at the intersection of AI and healthcare

  • Real ownership and visibility

  • High-impact role on a small, fast-growing team

Benefits

  • Competitive compensation, including meaningful equity

  • Medical, dental, and vision insurance for employee and dependents

  • Flexible PTO policy

  • Paid parental leave

  • Fertility and family-building stipend through Carrot

How we rate this

Research Scientist at Latent rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

NLPPyTorch

Also common in research scientist jobs at this level

Pay

This job starts at
$225k
Typical research scientist job
$191k

This posting starts 18% above the typical research scientist job. See research scientist jobs

Questions you could be asked

  1. What NLP problem have you worked on, and how did you measure whether it actually worked?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. How would you decide a model or AI system is ready to ship?
  4. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: NLP and PyTorch. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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