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Senior Research Engineer

Senior Research Engineer

Mem0San Francisco, CA, United States
1 day ago
Job type
  • Full-time
Job description

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 + streaming).
  • Clear, concise communication with stakeholders (engineering, product, GTM, and customers).
  • Nice to Have

  • Publications at venues like CVPR, NeurIPS, ICML, ACL, etc.
  • Experience with privacy-preserving ML (redaction, differential privacy, data governance).
  • Deep familiarity with memory / retrieval literature or prior work on memory systems.
  • Expertise with embeddings, vector-DB internals, deduplication, and contradiction detection.
  • Compensation Range

    $175,000.00 / yr - $210,000.00 / yr

    Seniority level

  • Mid-Senior level
  • Employment type

  • Full-time
  • Job function

  • Engineering and Information Technology
  • Industries

  • Technology, Information and Internet
  • #J-18808-Ljbffr

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    Research Engineer • San Francisco, CA, United States

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