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Must be located near the Bay Area, with reliable transport to San Francisco, CA. About Us We are a well-capitalized stealth startup building robotic foundation models and world models for Physical AI. Founded by researchers from leading AI labs, our team works across robot hardware, data, infrastructure, and machine learning. The Role We are hiring software engineers to build the systems around our robots: the data and infrastructure that our models are trained on, the tools our researchers and operators use every day, and the product our partners will eventually depend on. We are a small team, so everyone works broadly. This is an implementation role rather than a research role. You will not be designing models; you will be building the systems that let us train, evaluate, and deploy them. Responsibilities Design, build, and operate production software that our research and operations work depends on. Own systems end to end, from the conversation that surfaces the need through deployment, monitoring, and iteration. Work directly with ML researchers, robotics engineers, and robot operators, who all sit in the same room as you. Debug across boundaries, following a problem through services, storage, network, and hardware until it is actually understood. Build the logging, monitoring, and diagnostics needed to know whether a system is healthy. Re-architect what we have ahead of each order-of-magnitude increase in scale. Use AI coding agents to accelerate implementation, testing, debugging, and documentation. Improve reliability, performance, and maintainability as a matter of routine, not as a separate project. Qualifications BS or MS in Computer Science, Software Engineering, Computer Engineering, or a related field, or equivalent practical experience. Experience building and shipping production software that other people depend on. Strong proficiency in Python, plus Linux and Git. Experience designing and operating services, APIs, and databases in a cloud environment. Experience with cloud infrastructure e.g. AWS, GCP Strong cross-stack debugging and problem-solving skills. The ability to work from a described problem rather than a written specification. Experience using AI coding agents such as Claude Code, Codex, or comparable tools, including reviewing and validating generated code. Ownership and initiative: you find problems and solve them without waiting for direction. Comfortable working in a fast-moving environment and taking ownership of ambiguous problems. Nice to Have Experience with robotics, hardware, autonomous systems, or another physical-world product. Familiarity with robot data collection, teleoperation, or policy evaluation workflows. Familiarity with ML data pipeline and GPU training infrastructure What You Will Gain Build the software layer of a robot learning company from its earliest stage. Work across the complete stack, from raw robot data through foundation models to what customers touch. Room to move between focus areas as the company and your interests grow. Help shape the systems and engineering practices of an early-stage robotics company. Hiring Process Introductory video call Technical interview Optional one-day onsite assessment (paid at $45/hr) Initial six-month contract with strong potential for a longer-term opportunity Logistics & Benefits Location : San Francisco, CA (South Beach/SoMa) — on-site 5 days a week Schedule : Full-time, 40 hours/week, including a 30-minute lunch break Employment : W-2, facilitated through Hire.io Compensation : $45+/hour, negotiable based on experience
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.