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As seen at CES 2026, Atlas is the humanoid robot transforming what's possible in real-world manipulation and mobility. Our behavior development process is built on repeated iteration between data collection, policy training, hardware evaluation, and targeted diagnostics. We are seeking a software engineer to build the tools and infrastructure that power this cycle end to end. Your scope will span data pipelines, training infrastructure, evaluation systems, and the tooling that connects them, with the goal of reducing friction and increasing the throughput and quality of each iteration. You will work in close collaboration with research scientists, ML engineers, data operations teams, and robot demonstrators. How You Will Make An Impact Actively participate in ongoing R&D initiatives, collaborating closely with Research Scientists and Infrastructure Engineers. Develop tools to query and gain insights into data, training, and testing performance metrics. Analyze and track failures in experimental robot runs. Work with robot simulation software to develop scenarios, tests, and data collection tools. Build internal tools and platforms that accelerate the collect, train, and evaluate loop. Develop software that gives researchers and engineers immediate visibility into policy performance, data quality, and collection gaps. Work across hardware and simulation environments to support evaluation and rapid experimentation. Maintain and improve the code repository, ensuring its ongoing maintenance and improvement to meet evolving needs (CI/CD, testing, deployment). What We Are Looking For 3+ years of experience developing software for robotics, ML infrastructure, or related fields. Strong proficiency in Python, familiarity with C++ Experience building internal tools, dashboards, or GUI applications. Familiarity with ML workflows including training pipelines, experiment tracking, and dataset management. Experience working on real-world robotics systems, whether in industry, research, or academic settings. Experience with data analysis and visualization. Experience with cloud infrastructure, databases, Docker, and job orchestration. Strong communication and collaboration skills. Nice To Have MS in Robotics, Computer Science, Machine Learning, or a related field. Familiarity with behavior cloning, diffusion policies, or VLA/VLM architectures. Prior experience building or contributing to evaluation pipelines for ML or robotics systems. The base pay range for this position is between $154,000 to $190,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and an annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.
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.