# AI Research Engineer at Pathos > Hybrid · United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/ashby%3Apathos%3Afbec38e7-d55b-4bb3-8c74-644d75626c82 (read 2026-11-07). ## Facts (observed) - Company: [Pathos](https://alderhq.app/companies/pathos) - Location text: San Francisco - Where it can be done from (inferred): Hybrid · United States (evidence: "Location: San Francisco") - Posted: 2025-12-02 (340 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/pathos/fbec38e7-d55b-4bb3-8c74-644d75626c82 - Skills listed (inferred): LLMs ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (SF Bay Area, n 461): p25 $200k, median $250k, p75 $300k ## Description (the employer's text) ### Mission The Path is a research lab and consumer health company on a mission to provide therapy-grade help and coaching for anyone, anytime. Over 3 billion people a year have a problem large enough to warrant therapy but the barriers to access - around price, time, geography, stigma, and language - are so large that less than 10% of these people are getting the help they need. The Path exists because help shouldn’t depend on privilege, because intelligence should serve humanity, and because clarity is the first act of care. Our purpose-built AI therapists provide evidence-based mental health support delivered through artificial intelligence, designed to get smarter with every session. The Path was built by a neuroscientist who understands how the brain actually changes. Most AI chat tools were not. Every role here moves that work forward. Join a small, passionate in-person team in San Francisco building the AI and the clinical research behind it! ### The Opportunity Design, train, ship, iterate on, and innovate on the AI brains behind The Path’s AI Therapist. Combine research, data science, and engineering to create models, orchestration, and evaluation systems that make therapy conversations deeply effective, clinically grounded, and safe. Note - Below contains the outcomes and competencies for the team. If you bring standout strengths in some areas but not all, you are still encouraged to apply. ### Responsibilities Improve quality of AI Therapy: Deliver measurable improvements in conversation quality, therapeutic alliance, and user outcomes through fine-tuning strategies, training data curation, building RL environments, new model architectures and other AI innovations. Improve evaluation of AI quality: Improve on and maintain a robust eval stack that includes scripted tests, LLM-as-judge evaluations, human ratings, and safety checks. Improve automated regression testing, detection of defects, and observability (eg dashboards). Own AI system. Build, maintain, and iterate on the production codebase that delivers AI therapy and supports the evaluation and iteration of our AI. Productionize Models and Pipelines. Own The Path from notebook to production: training jobs, model packaging, deployment, monitoring, and rollback strategies. Keep latency, reliability, and cost within agreed budgets while enabling rapid iteration on new ideas. Safety, Alignment, and Clinical Guardrails Work with clinicians and internal experts to encode clinical guidelines into prompts, reward functions, tools, and filters. Proactively identify and reduce harmful or low-quality behaviors through targeted experiments, red teaming, and mitigations. Own Research Roadmap and Experiment Velocity Run high-quality experiments from hypothesis to analysis to improve our understanding of what matters and what works. Shape and execute a focused R&D roadmap. Collaboration with Clinicians, Product, and Engineering. Translate product and clinical requirements into concrete model and system changes. Partner with full-stack product engineers so that new AI capabilities are easy to integrate and maintain in the product. ### Competencies LLM and Applied ML Depth. Demonstrates strong experience with large language models, including fine-tuning, training data design, and model selection. Knows how to move core metrics on conversation quality and user outcomes, rather than chasing generic benchmarks. Can look at evals, transcripts, and metrics and quickly form grounded hypotheses for improvement. Ships clean, maintainable, quality code. No only do you know how transformers work, but you are also an engineer that has experience shipping production-level code and/or maintaining an AI system in production. Data Engineering Skills. Can set up production-level data pipelines for training new models, evals, analysis, etc. Scientific Mindset. You formulate hypotheses, and you are good at evaluating them (eg through experiments, data analysis, etc). You are consistently learning at the cutting edge, and you’re able to leverage and communicate those learnings to make the entire company more successful. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Apathos%3Afbec38e7-d55b-4bb3-8c74-644d75626c82 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.