Member of Technical Staff, Forward Deployed Engineer

Skills

About the Role

You'll work directly with strategic customers to understand their problems and turn them into research questions and working systems built around world models. You'll fine-tune and adapt models, design experiments, build conditioning and control methods, and develop evaluation frameworks. You'll build end-to-end prototypes, diagnose failures in deployed systems, and create feedback loops with core research teams. Expect to work on-site with customers when it helps and to communicate clearly with both technical teams and senior stakeholders.

Requirements

• Deep technical experience in world models, generative video, multimodal learning, robotics, autonomous systems, reinforcement learning, computer vision, or large-scale machine learning
• Ability to move from ambiguous problem to experiment, prototype, and deployed system
• Ability to modify models and build systems around them across training, post-training, inference, data pipelines, evaluation, and application code
• First-principles problem solving
• Effective collaboration with customers and external partners
• Ability to manage competing priorities
• Willingness to travel or be embedded with partner teams
• In office at least three times a week

Responsibilities

• Embed closely with strategic customers to understand workflows, constraints, data, and high-value problems
• Identify where world models can create a step-change in capability across robotics, simulation, autonomy, training, and interactive media
• Translate loosely defined customer goals into research and engineering problems, hypotheses, prototypes, and deployment plans
• Adapt and extend models through fine-tuning, post-training, conditioning, controllability, inference optimization, and learned control policies
• Build end-to-end prototypes connecting world models to customer data, tools, simulators, hardware, and production systems
• Design application-specific evaluations for usefulness, controllability, consistency, and reliability
• Diagnose failures in deployed systems across data, modeling, training, inference, evaluation, and product design
• Create fast feedback loops between customer deployments and core research teams
• Work with researchers, engineers, product teams, and customer stakeholders from exploration through deployment
• Develop reusable infrastructure, methods, and playbooks for future deployments
• Communicate technical decisions and experimental results to technical teams and senior customer stakeholders
• Publish or share case studies while protecting customer confidentiality

Benefits

• Equity