# Senior Research Engineer

**Company:** [Mem0](https://hotfix.jobs/companies/mem0)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $175k – $210k/yr
**Skills:** RAG, PyTorch, Python, LLMs, vLLM, Information Retrieval, Vector Databases, Embeddings, Fine-Tuning, A/B Testing, Data Pipelines
**Posted:** 2026-01-18

> Owns end-to-end lifecycle of memory features in AI systems, fine-tuning LLMs for extraction/updates/forgetting, implementing research papers, building large-scale evaluations, and shipping production models with engineering. Requires RAG/IR experience, PyTorch proficiency, and production ML expertise.

## Job Description

## 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.

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**Apply:** https://hotfix.jobs/jobs/bc4a4882-5de9-4979-82ef-821eed4c80cd
**Canonical:** https://hotfix.jobs/jobs/bc4a4882-5de9-4979-82ef-821eed4c80cd