Staff Ml Engineer
2 semanas atrás
Company DescriptionYuna's mission is to radically transform the way mental health support is accessed and delivered. By providing 24/7 instant and private support at the push of a button, we aim to address the significant gaps in mental health care accessibility. In a system where waiting times for therapists can reach up to 48 days and many people can't even afford care, Yuna is the answer to immediate mental health support needs.We're growing quickly, and every person who joins us plays a pivotal role in shaping the future of mental health technology.Position OverviewYou'll own Yuna's core conversational intelligence (i.e. spanning retrieval, memory, safety, evaluation, and post-training). You'll ship user-visible improvements quickly while raising the bar on empathy, reliability, and guardrails. This is a hands-on staff-level role: equal parts research-to-production and platform thinking.What you'll doLead the end-to-end model lifecycle of Yuna's conversational AI: problem framing ? data curation ? modeling/fine-tuning/post-training ? evals ? rollout ? monitoringWork closely with clinical psychologists (both internal and external to Yuna), ensuring the efficacy of Yuna's conversational AIDesign agentic flows (tool use, planning, multi-turn memory) and safe retrieval for mental-health use casesBuild and own the evaluation flywheel: benchmarks, judge models, rubrics for conversational quality, ability to help, safetyImplement alignment & safety layers (e.g., self-harm detection, red-teaming, refusal strategies, escalation paths) tuned to clinical guidelinesOptimize for latency, cost, and qualityPartner tightly with product, sales, and users to scope new features andEstablish LLMOps: datasets, prompts/checkpoints/versioning, observability, drift monitoring, and incident response for model qualityWhat you'll bring5+ years in ML/AI with 3+ shipping LLM/NLP systems in productionDeep skill in Python and modern deep learning stacks (Py Torch/JAX/Tensor Flow), retrieval/RAG, embeddings, reranking, and long-context summarizationExperience building agentic systems (tool calling, decomposition, memory) and rigorous eval harnesses (offline + online)Strong product sense; you care about user outcomes, not just model metricsComfort working with ambiguity and creating systems 0 to 1Location: Remote (work from anywhere, with at least 6 hours overlap with PST)Employment Type: Full TimeWhat We OfferCompetitive salary (based on experience) + equity optionsRemote-first culture with flexibilityA fast-growing, talented, and empathetic team dedicated to transforming mental health careThe opportunity to make a real impact on the world, building cutting-edge AI systems that improve lives every day
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