We're working with an Intel Capital backed AI Startup in San Francisco that’s building a multimodal generalist agent at the frontier of AI, merging cutting-edge neural architectures with long-term memory, reinforcement learning, and continual adaptation.
The team includes ex-DeepMind, Nvidia, Anthropic and Apple professionals, and they are operating at the cutting edge of the AI space.
The company is extremely well-backed, with $100M in Series A funding, and was founded by an entrepreneur with 2 successful exits, including selling his startup to Salesforce for $500M.
They’re hiring a Machine Learning Data Engineer to:
- Design and build large-scale retrieval pipelines (embeddings, vector search, similarity, semantic ranking) that drive agentic workflows
- Architect and implement robust data systems and tooling that power memory, long-term state, and multimodal inference
- Collaborate with ML teams to integrate retrieval + data infrastructure with LLMs and vision-language models to enable multi-step reasoning, planning, and autonomous action
Why join:
- Work on the leading edge of agentic AI, you’re not just tuning models, you’re building the data backbone of autonomous systems
- Deep bench of talent: engineers and researchers from top AI labs
- Strong equity stake: you’ll have a real ownership position in a company poised for meaningful scale
TC: 250-350k base, up 1 million total w/equity
