Lead research on hardware intelligence systems, developing evaluation frameworks, training pipelines, and agent integration for physical engineering contexts.
Responsibilities
Find where our agents fail on real hardware work
Turn failures into evals, environments, and training data
Build graders and verifiers that check agent work against measured data
Fix issues by adjusting prompts, tools, or context, fine‑tuning, running RL, or distilling models
Prototype across research bets such as hardware context for agents, computer use in engineering tools, linking simulation to physical tests, coordinating collections of agents, and edge intelligence
Requirements
Nice to have: post‑training (SFT, RL from feedback, distillation)
Setting the research agenda for Hardware Intelligence, building agents that reason over hardware context, and leading the post-training of AI models.
Responsibilities
Set the research agenda for Hardware Intelligence: pick the problems, place the bets, and define what winning looks like each quarter.
Figure out how to store and represent hardware context, so agents reason over telemetry, test campaigns, requirements, designs, and simulations instead of retrieving them.
Teach agents to work the tools engineers already use, from CAD to simulation to analysis software, through computer use.
Connect simulation to the physical world: calibrate simulations against measured results, and use simulations to plan and explain tests.
Build distributed intelligence: collections of agents that coordinate across programs, fleets, and teams.
Senior product engineer to own and deliver large problems in the Central Ops Engineering space. You will build internal web apps and automations that agents use every day, and help shape how the team uses AI coding tools.
Responsibilities
Build internal web apps and automations that agents use every day
Help shape how the team uses AI coding tools
Handle complaints processing efficiency
Build signals for fraud and fincrime investigation
Looking for a person with extensive experience in vibe coding to lead a practical online course called 'Vibe coding: applications without programming'. The role involves guiding non-technical participants (product managers, designers, etc.) to build functional web apps and apps using AI prompts.
Responsibilities
Share professional knowledge and experience from building practical applications using AI.
Prepare and lead engaging online lessons combining theory, live app building, and interactive exercises.
Support, motivate, and guide participants throughout the course, helping them with installation, errors, or deployment issues.
Create an open and welcoming atmosphere for participants from various backgrounds.
Keep the curriculum up to date by following news in vibe coding tools and best practices.
The annual base salary for this role is between $175,000 - $210,000, depending on experience, with the opportunity for a performance-based bonus, company equity, 401(k) matching, paid parental leave, flexible and generous time off, work-from-home flexibility, and subsidized health benefits.
Responsibilities
Own identity data and design data models and matching logic
Build partner data mappings and maintain identifier mappings
Build and run production pipelines
Build privacy controls into identity data
Create data quality frameworks and anomaly detection
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