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The Memory layer for your AI apps and agents.
Senior Research Engineer
Location
California + 1 moreAll locations: California | Canada
Posted
128 days ago
Salary
$0
Seniority
Senior
Job Description
Senior Research Engineer
Mem0
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
Job Requirements
- 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.
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