Founding AI Research Lead - Agentic AI Lab

Fabrion • San Francisco Bay Area, CA

1d • Onsite

About The Position

Fabrion is designing the future of enterprise AI infrastructure, grounded in agents, knowledge graphs, and multi-tenant governance. We are working on research inside the Agentic AI Lab to train and evaluate specialized models for mission-critical enterprise work. The direction is specific and ambitious. We share the full thesis under NDA during the interview process. The program has committed design partners with production data access, dedicated compute, a benchmark-first plan with clear go and no-go gates, and a platform team that has already built the governance and serving layer your models will run behind. This is full-cycle research: problem formulation, data, training, evaluation, and deployment, with your name on the results.

Requirements

• Hands-on experience training sequence models, owning the tokenizer, the training loop, and the evaluation, not only fine-tuning through APIs
• Strong background in at least two of: reinforcement learning (especially offline and imitation settings), sequence decision modeling, structured or constrained generation, learning from event and log data
• A track record of shipping research into a product or landing a rigorous benchmark result
• PhD in machine learning or a closely related field, or an equivalent research record
• Comfortable as the most senior researcher in the room: setting direction under ambiguity and writing decisions down
• Rigor over hype: you distrust your own results until the baselines agree
• A teacher's instinct: part of this role is turning strong engineers into researchers

Nice To Haves

• PyTorch, the Hugging Face ecosystem, experiment tracking and reproducible training pipelines, modern cloud data warehouses, evaluation harness engineering

Responsibilities

• Own the research agenda: model and training design, evaluation protocol, and the publication plan
• Take models from public benchmark results to live customer shadow deployments, with gates you define and defend
• Set the benchmark discipline: strong baselines first, published comparables cited, results that survive scrutiny
• Lead and grow a small team (ML engineer, data engineer, contractors) and pair closely with the founders and platform team
• Write technical plans internally and papers externally when results warrant it

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree