About the Role:

This is a deeply cross-functional, execution-oriented role at the center of our model research, robotics stack, and partner deployments. As a Field Applications Engineer, you will be the technical owner of our relationships with a dedicated set of partners. You will turn robots, data, models, and evaluations into a tight, high-velocity feedback loop to support successful partner deployments. This role is responsible for supporting making real-world deployments work reliably, on partner hardware, at partner sites.

You will be a critical part of the team improving Generalist’s models and landing the impact of those improvements for partners, including experimentation and analysis for modeling science. You will help design tasks, coordinate data collection, kick off training jobs, run evaluations, analyze results, and ensure robots are physically ready for live operation. You'll spend time onsite with partners, understanding their environment, building trust, troubleshooting in real time, and translating partner needs back into our roadmap. You may build physical benchmarks, lightly modify hardware setups, test third-party tooling, and write documentation that enables others to replicate and scale your work.

You'll be responsible for:

• Being the dedicated technical point of contact for assigned partner accounts

• Spending time onsite at partner facilities as needed, meeting partner expectations for responsiveness and reliability

• Executing and analyzing a range of experiments and deployment tasks on various robot platforms

• Collaborating closely with research and partnerships teams on results, synthesizing and interpreting findings for both internal and partner audiences

• Designing new tasks and benchmarks to evaluate model capabilities in partner contexts

• Procuring materials and building lightweight physical benchmarks or fixtures as needed

• Ensuring robots are properly configured, calibrated, and ready for rollouts and evaluations at partner sites

• Supporting partners in designing and executing structured evaluations and measuring real-world success rates against partner success criteria

• Analyzing results and closing feedback loops with both ML researchers and partner stakeholders

• Beta testing internal and third-party tools, capturing partner feedback on these tools and closing feedback loop with internal teams

• Supporting clear documentation and playbooks so others (internal and partner-side) can reproduce workflows

• Identifying operational bottlenecks and improving system throughput end-to-end

• Providing partner-facing guidance, training, and support to drive partner success

You might thrive in this role if you:

• Enjoy being the face of a technical team in front of a partner, not just behind the scenes

• Are continuously diligent in the face of seemingly repetitive, but subtly changing task evaluations

• Have hands-on experience with robot data collection, evaluation, or deployment

• Have conceptual understanding of the full modern ML training, fine-tuning, and inference life cycles

• Are comfortable running experiments and tracking real-world metrics across multiple model variants

• Enjoy operating across software, hardware, and physical systems — and across company lines with partner teams

• Have some exposure to basic EE/ME tasks (wiring, mounting sensors, assembling fixtures, debugging hardware)

• Are highly organized and can coordinate multiple moving parts (and multiple stakeholders) simultaneously

• Write clear, structured documentation

• Are great at capturing bug reports and troubleshooting high-tech systems, and teaming on root-cause analysis for issues

• Prefer execution and iteration speed over theoretical purity

• Like being the person who "just makes it work" — for both your team and your partner's

• Are comfortable with regular travel and significant time onsite at partner locations

What This Role Is Not

This role sits at the intersection of ML, robotics, operations, and partnerships. You are ensuring our systems run end-to-end in the real world — on someone else's floor — and improving them through tight execution loops with the partner in the room. You will be part of the ML and commercial teams, working closely with both. However:

• This is not a pure ML research role focused on designing new model architectures or advancing core learning algorithms

• This is not a large-scale infrastructure engineering role building distributed systems, databases, or UI platforms

• This is not a pure robotics controls or firmware engineering role

• This is not a traditional account management or sales role — the value you bring is technical depth applied in service of partner success

If you are most excited by hands-on full-stack systems work, cross-functional execution, and making partners successful while accelerating the entire system, this role may be a strong fit.

About Generalist

At Generalist, we are on a mission to make general-purpose robots a reality. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.

We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.

The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.