Mem0
Senior Research Engineer
3w ago
175000 –250000 USD / yearUSASeniorpythonmodel trainingfine-tuningexperimental designevaluation metricsapi design
Own the end-to-end lifecycle of memory features including model fine-tuning, evaluation, and production deployment.
Responsibilities
- 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.
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 language and/or retrieval and generation 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 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.
Other
- 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.
- We're building the memory layer for AI agents. Think long-term memory that enables AI to remember conversations, learn from interactions, and build context over time. We're already powering millions of AI interactions for our enterprise customers and our open-source community (150k+ devs and counting!). We are backed by top-tier investors through a $25M Series A & Seed.
- Office-first collaboration - We're an in-person team in San Francisco. Hallway chats, impromptu whiteboard sessions, and shared meals spark ideas that remote calls can't.
- Velocity with craftsmanship - We build for the long term, not just shipping features. We move fast but never sacrifice reliability or thoughtful design - every system needs to be fast, reliable, and elegant.
- Extreme ownership - Everyone at Mem0 is a builder-owner. If you spot a problem or opportunity, you have the agency to fix it. Titles are light; impact is heavy.
- High bar, high trust - We hire for talent and potential, then give people room to run. Code is reviewed, ideas are challenged, and wins are celebrated—always with respect and curiosity.
- Data-driven, not ego-driven – The best solution wins, whether it comes from a founder or an engineer who joined yesterday. We let results and metrics guide our decisions.