
Effortless information recall powered by AI
Mem0 is an AI-powered memory augmentation platform headquartered in San Francisco, California. The company leverages advanced natural language processing to transform meetings, documents, and conversations into a searchable knowledge base, enhancing information recall for individuals and teams. With...
Mem0 offers competitive equity options, flexible PTO policies, and a remote work environment to support work-life balance....
Mem0 fosters a culture of innovation and agility, emphasizing the importance of leveraging AI to enhance human capabilities and streamline workflows....

Mem0 • San Francisco Bay Area
Mem0 is seeking a Senior Research Engineer to own the lifecycle of memory features from research to production. You'll fine-tune models and implement ideas from research papers using Python and PyTorch. This role requires experience in information retrieval and model training.
You have a strong background in AI research and engineering, with experience in the end-to-end lifecycle of memory features — from research to production. Your expertise includes fine-tuning models for memory extraction, updates, and conflict resolution, and you are adept at turning customer pain points into actionable research hypotheses. You have a solid footing in experimental design and iteration, which allows you to effectively prototype and benchmark ideas from academic papers against real-world applications.
Your programming skills are robust, particularly in Python, and you have deep experience with PyTorch. You are familiar with modern serving frameworks and have a keen understanding of how to build evaluation metrics at scale. Your experience in information retrieval, including retrieval, ranking, and query understanding, has equipped you to handle complex challenges in real products.
You are comfortable collaborating with various stakeholders, including engineering, product, and customers, to ensure that the solutions you develop are not only technically sound but also aligned with user needs. Your ability to communicate complex ideas clearly and effectively makes you a valuable team member.
You have publications in reputable venues such as CVPR, NeurIPS, or ICML, showcasing your contributions to the field. Experience with privacy-preserving machine learning techniques, such as redaction and differential privacy, is a plus. A deep familiarity with memory and retrieval literature, along with prior work on memory systems, will set you apart.
In this role, you will own the end-to-end lifecycle of memory features, ensuring that they meet the highest standards of latency, reliability, and cost-effectiveness. You will fine-tune and train models for various memory-related tasks, iterating based on data and outcomes to continuously improve quality. Your work will involve reading, reproducing, and implementing research findings, quickly prototyping ideas, and benchmarking them against established baselines.
You will build evaluation metrics at scale, including automated relevance, accuracy, and consistency metrics, as well as gold sets and online A/B testing frameworks. Collaborating closely with customers, you will uncover pain points and validate solutions through field trials, ensuring that the products you develop truly meet user needs.
Partnering with engineering teams, you will design APIs and data contracts, plan safe rollouts, and maintain state-of-the-art performance at scale. Your role will require you to stay updated with the latest advancements in the field and apply them to enhance the products you work on.
At Mem0, you will be part of a dynamic team that values innovation and collaboration. We offer a competitive salary and benefits package, along with opportunities for professional growth and development. You will have the chance to work on cutting-edge technology that impacts real-world applications, contributing to the advancement of memory systems and AI research. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.
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