SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Lightfield is reimagining CRM as a world model of a business by learning from emails, meetings, and customer conversations to build a living understanding of how companies work. The company has raised over $70M from top-tier VCs (Andreessen Horowitz, Coatue, Maverick Ventures, Greylock) and has already attracted 5,000+ companies since its November launch. The founding team previously built Tome (25M+ users) and brings experience from Llama, Instagram, Google, and Salesforce.
Lightfield Research is launching a new division focused on frontier research in simulation, world modeling, and self-improvement. You will report directly to Ves Stoyanov, co-founder and Chief AI Officer (formerly Facebook AI, co-author of RoBERTa and XLM-R). You'll own research projects from conception through measurable product impact and publication, working alongside AI engineers who productionize research and GTM experts who define tasks and quality metrics.
Key responsibilities include: leading research projects in evaluation, benchmarks, deal prediction, simulation, and self-improvement; designing empirical evaluations using LLM-as-judge, rubric-based grading, offline replay, and A/B testing on production and offline data; building benchmarks for core GTM tasks (list building, CSV imports, mail intelligence, record updates, outbound); creating simulated companies with known ground truth to evaluate the full system end-to-end; developing techniques for continuous self-improvement at world, company, and user levels (reinforcement learning, fine-tuning); modeling deal probability and shipping as product features; optimizing cost-quality trade-offs across the AI system; publishing research blog posts, open benchmarks, arXiv reports, and conference presentations; and recruiting and mentoring research team members.
You'll help shape the lab's research agenda, culture, and reputation as it grows. This is a high-impact role at the intersection of cutting-edge AI research and real business applications.
REQUIREMENTS:
- 7+ years of applied research experience in ML or NLP (industry or academia)
- PhD or MS in Computer Science, Machine Learning, or related field (or equivalent research experience)
- Track record of shipped or published research: papers, open-source models, datasets, or benchmarks
- Deep hands-on experience with LLMs, including evaluation, agent design, and retrieval
- Post-training experience (SFT, RL, preference optimization) is a plus
- Rigorous experimental design; ability to distinguish real improvements from noise
- Strong Python; comfortable in production codebases (TypeScript, Node.js, PostgreSQL) alongside engineers
- Ability to drive ambiguous problems independently and balance ambitious goals with frequent, visible results
- Clear communication to technical and non-technical audiences (writing and presentations)
- Energized by building AI that businesses depend on
NICE TO HAVE:
- Experience building simulations, synthetic data, or RL environments
- Experience with forecasting or predictive modeling on business data
- Experience creating benchmarks adopted by others
