Research Member of Technical Staff- Applied Research

What You'll Do

• Work directly with customers and partners to understand application requirements and translate them into concrete model adaptation strategies
• Fine-tune and adapt our foundation world models for domain-specific tasks, environments, and operational constraints
• Design and run targeted experiments to evaluate model performance against customer-defined success criteria
• Build application-specific evaluation benchmarks and testing frameworks to validate model behavior in real customer environments
• Identify gaps between general-purpose model capabilities and the requirements of specific use cases, and drive research to close them
• Collaborate with the core research team to surface patterns and insights from customer deployments that inform foundational model development
• Communicate technical findings clearly to both technical and non-technical stakeholders

What We're Looking For

• Strong ML research and engineering skills with hands-on experience fine-tuning or adapting large models
• Ability to move fluidly between customer requirements and technical implementation
• Solid understanding of modern ML pipelines: pre-training, fine-tuning, evaluation, and deployment
• Comfort working across teams - research, engineering, and customer-facing functions
• Strong communication skills: ability to explain model behavior and tradeoffs to non-technical audiences
• Experience in a customer-facing, applied research, or solutions engineering role
• Staff-level candidates are expected to define technical direction and drive research strategy independently; senior/MTS candidates execute complex projects with strong fundamentals and growing scope

Nice to Have (But Not Required)

• Experience adapting foundation models (LLMs, VLMs, or policy models) to domain-specific applications
• Familiarity with one or more relevant verticals (e.g., logistics, manufacturing, warehouse automation, agriculture)
• Familiarity with inference optimization and runtime constraints (latency, memory, hardware targets) - sufficient to work alongside inference engineers, not own it
• Experience with sim-to-real transfer or adapting models trained in one environment to operate in another
• Hands-on experience with real robot deployments in production or near-production settings
• PhD or strong research background in ML, Robotics, or a related field

Why This Role

• Rare combination of research depth and direct customer impact - you see your work matter in the real world
• Surface insights from real-world deployments that feed back into foundational model development
• Work across industries and applications with significant variety in problems and environments
• High visibility within the company as the bridge between our core models and the customers who use them