Senior Research Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Mental health support

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Relocation assistance

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Childcare support

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Onsite From the posting source checked Jun 20, 2026

In-office days

5 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Senior Research Engineer San Francisco Bay Area | OnSite Role Summary: Own the end-to-end lifecycle of memory features-from research to production. You'll fine-tune models for extraction, updates, consolidation/forgetting, and conflict resolution; turn customer pain points into research hypotheses; implement and benchmark ideas from papers; and ship with Engineering to SOTA latency, reliability, and cost. You'll also build evaluation at scale (offline metrics + online A/Bs) and close the loop with real-world feedback to continuously improve quality. What You'll Do: - Fine-tune and train models for memory extraction, updates, consolidation/forgetting, and conflict resolution; iterate based on data and outcomes. - Read, reproduce, and implement research: quickly prototype paper ideas, benchmark against baselines, and productionize what wins. - Build evaluation at scale: automated relevance/accuracy/consistency metrics, gold sets, online A/B & interleaving, and clear dashboards. - Work closely with customers to uncover pain points, turn them into research hypotheses, and validate solutions through field trials. - Partner with Engineering to ship: design APIs and data contracts, plan safe rollouts, and maintain SOTA latency, reliability, and cost at scale. Minimum Qualifications - Experience in RAG or information retrieval (retrieval, ranking, query understanding) for real products. - Model training/fine-tuning experience (LLMs/encoders) with a strong footing in experimental design and iteration. - Strong Python; deep experience with PyTorch and familiarity with vLLM and modern serving frameworks. - Built evaluation for complex vision-and-language tasks (gold sets, offline metrics, online tests). - Able to orchestrate data pipelines to run these models in production with low-latency SLAs (batch +

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