AI Researcher

AI Researcher

Location: Seattle, WA (On-site)

Blue Pill AI builds AI Consumers — digital twins of real audiences trained on social, survey, and research data that replicate how humans actually think, decide, and behave. Brands use Blue Pill to test product concepts, packaging, messaging, and strategy in minutes instead of months.

Our models are grounded in real human data and validated against live human panels, achieving up to 93% accuracy in replicating human responses. We obsess over model behavior, failure modes, and cultural drift — continuously refining systems so they stay aligned with how people actually think in the real world.

We’re not building demos. We’re building a new category of consumer intelligence.

• Design, experiment with, and optimize LLM-based systems for simulating human judgment, preference, and decision-making
• Go beyond “prompting” — work with fine-tuning, embeddings, retrieval, memory, reasoning scaffolds, and evaluation frameworks
• Design and run rigorous experiments to measure model improvements using sound experimental design and statistical analysis
• Build and iterate on model evaluation pipelines to measure realism, consistency, bias, drift, calibration, and alignment with human data
• Analyze LLM failure modes and edge cases, including issues related to uncertainty, truthfulness, and overconfidence
  , and design interventions to fix them
• Translate research insights into production-ready systems used by real customers
• Collaborate closely with product, behavioral science, and engineering to ship end-to-end features
• Stay close to the frontier: experiment with new models, papers, and techniques — and decide what’s actually worth using

Must-Have

• Deep hands-on experience working with LLMs (OpenAI, Anthropic, open-source, or similar)
• Strong intuition for how LLMs behave internally — not just how to use them
• Experience building real products or systems with LLMs in production
• Strong foundation in NLP, neural networks, and machine learning fundamentals
• Proficiency with Python and modern ML tooling
• Demonstrated proficiency in experimental design and statistical analysis for evaluating and improving models
• Understanding of uncertainty estimation, calibration, and truthfulness in model outputs
• Comfort moving between messy experiments and clean, scalable implementations

• Experience working in deep tech environments (hard problems, long feedback loops, non-obvious failure modes)
• Experience training LLMs from scratch or at significant scale
• Experience with fine-tuning, RLHF-style techniques, or large-scale evaluation systems
• Familiarity with PyTorch, Tensor Flow, JAX, or distributed training setups
• Experience working with noisy, real-world human data

• This is not a purely academic research role
• This is not a “AI engineer” position
• This is a builder–researcher role for someone who loves understanding models by playing with them
• Curiosity, taste, and judgment matter as much as credentials

• (Not required) Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field preferred
• Exceptional self-taught engineers with strong real-world experience are encouraged to apply

Salary: $160K – $200K, Meaningful Equity, 100% health benefits