Job Description
About Frontier Machines
\n
We believe technology can unlock abundance and shared prosperity. While AI has transformed the digital world, we're bringing it into the physical one, starting with manufacturing. We deploy fully autonomous robotic systems that increase throughput, reduce costs, and enable our customers to scale.
\n
Our system consists of two low-cost, compliant 6-DOF robotic arms equipped with wrist-mounted fisheye cameras and jaw grippers. These robots are powered by large vision-language-action models (1B+ parameters), trained on real-world data collected from customer sites and deployed locally for real-time control.
\n
About the Role
\n
We're hiring a Solutions Engineer to own customer deployments from first visit to production. You'll figure out which tasks robots should do, estimate the ROI, build the physical setup, work out how the robot should do the task, and lead a remote operator team to bring it to production.
\n
This is a hands-on, on-site role based out of our Redwood City, CA office. About half our customers are within a 1–2 hour drive, so expect to spend much of your week driving to sites across the Bay Area and Northern California. The other half are elsewhere in the US and require flights and multi-day trips. We're an early-stage company moving fast, and we want people who are eager to take ownership.
\n
Why This Role is Different
\n
- \n
- You own deployments end to end, from first visit to production
- You'll directly shape the product through field feedback
- Your work directly generates revenue within weeks
- You'll lead a team of remote robot operators, not just operate robots yourself
- You'll work in messy, real-world factories, not controlled labs
\n
\n
\n
\n
\n
\n
Who Should NOT Apply
\n
- \n
- People who want a predictable, desk-based routine
- People looking for a 9-to-5: expect long or irregular hours to match customer shifts, train operators, and hit tight deadlines
- People who don't want to drive regularly to local customer sites or spend 2–3 week stretches on-site with customers across the US
- Engineers who prefer to design and hand off rather than build with their own hands
\n
\n
\n
\n
\n
Who You Are
\n
Capabilities
\n
- \n
- You like building things: you're comfortable with CAD, 80/20, 3D printing, and hand tools
- Personable and clear. You can walk a plant manager through an ROI estimate and train a new operator on a task
- Willing to learn AI coding agents like Claude Code to run scripts and tools; Linux familiarity is a bonus, not a requirement
- Good hand-eye coordination and the patience to practice something repeatedly until you master it, from sports, gaming, or similar activities
- Comfortable spending extended stretches in a VR headset teleoperating robots
- Able to lift up to 45 pounds to set up robots and frames on-site
- A valid driver's license, your own car, and auto insurance (mileage is reimbursed)
\n
\n
\n
\n
\n
\n
\n
\n
Interests
\n
- \n
- You're excited about AI, robotics, and manufacturing and working at their intersection
- You thrive in fast-moving, ambiguous environments and take ownership of outcomes
- You enjoy working with new people and have strong listening skills
\n
\n
\n
\n
What You'll Do
\n
- \n
- Discovery: Visit customer facilities, perform target tasks by hand, measure the line setup, and collect product samples. Identify robot-friendly tasks and ways to re-factor assembly lines for automation, and build ROI estimates that help customers decide what to automate.
- Figure out the task: Robots aren't people, so tasks need adapting. Teleoperate in VR to test approaches, and design the setup that makes the task work: robot placement, 80/20 mounting frames, and jigs and fixtures you CAD and 3D print.
- Lead the operator team: Hand the task off to a 2–8 person remote operator team. Train a lead operator on your approach, have them train the rest of the team, and check in to make sure everyone is doing the task consistently and correctly.
- Deploy and iterate: Oversee your operator team as they collect tens to hundreds of hours of data. Use it to fine-tune our foundation policy for the task, roll it out, and iteratively refine it until the robot's performance meets customer expectations.
- Maintain and scale: Fix hardware and setup issues, return to sites for maintenance, and bring new tasks online with existing customers.
\n
\n
\n
\n
\n
\n
What Success Looks Like
\n
- \n
- The main measure: customer leads you've turned into successful production deployments
- You can independently scope a customer's line, build the setup, and get a task working
- Your operator teams run tasks without needing you day to day
- You've contributed to improving our deployment playbooks
\n
\n
\n
\n
\n
Example Backgrounds that Might be a Good Fit
\n
- \n
- A mechanical engineer with 0–3 years of experience who did FSAE, FIRST Robotics, or similar hands-on build projects
- A manufacturing or applications engineer who has worked on factory floors and enjoys customer-facing work
- A new grad with lots of shop time, CAD projects, and a knack for teaching others
\n
\n
\n
\n
Expected Compensation
\n
- \n
- $80,000–$100,000/year base salary + equity + benefits + bonus
\n