As a Robotics ML Engineer at Rerun, your responsibilities will involve building and deploying ML-heavy products in the physical world. You will construct data pipelines for robotics imitation learning, develop data cleaning workflows, and create comprehensive educational content that aids our customers. Additionally, interacting with our vibrant community to understand their needs and feed learnings back into the core products will be key aspects of your role.

Rerun seeks a Robotics ML Engineer with an ownership mindset and a strong track record of successful projects. You should possess broad knowledge of machine learning, robotics, and 3D geometry, along with skills in Python and familiarity with C++ or Rust. Experience with MLOps and systems for data processing and running on GPUs is highly valued. An eagerness to teach and contribute to the community is also essential.

At Rerun, we provide robust support for our Robotics ML Engineers by fostering a collaborative environment and offering competitive compensation packages, including cash and equity. We prioritize well-being with six weeks of paid vacation and ensure you have the hardware and software you need. Our emphasis on synchronous collaboration means that you will always feel connected to the team, even while working remotely.

As a Robotics ML Engineer at Rerun, you will work extensively with technologies including Python, and possibly C++ or Rust. You will engage with MLOps tools, manage data pipelines, and use frameworks like PyTorch alongside NVIDIA DALI. Familiarity with Linux systems and tools for robotics and data management will also be crucial in your role.

The culture at Rerun is supportive, innovative, and collaborative. We meet in person quarterly to strengthen our connections and ensure everyone is aligned. During working hours, we expect team members to be available between 1:30 and 5 pm CET for synchronous collaboration. We value agency and responsibility, encouraging each team member to contribute positively to our projects.

Discuss a specific project, detailing the objectives, challenges faced, and how you utilized machine learning. Highlight the technologies used and the impact of your work on the project outcomes. Focus on your problem-solving techniques and what you learned from the experience.

Explain your approach to building and managing data pipelines, including data collection, cleaning, and validation. Share tools or frameworks you’ve utilized, and describe how you optimize these processes for efficiency and reliability in a robotics setting.

Community interaction is essential for feedback and improvement. Share how you engage with users and gather insights. Discuss examples where community input led to enhancements in projects or educational resources you developed.

Discuss the MLOps tools and practices you’ve implemented, focusing on data versioning, model deployment, and monitoring. Mention any continuous integration frameworks you've used and how they improved the reliability of robotics projects.

Talk about your process for creating tutorials, blogs, or videos, emphasizing clarity and accessibility. Provide examples that demonstrate how you've effectively communicated complex topics to different audiences.

Identify key performance indicators such as accuracy, efficiency, and user engagement. Discuss how you establish benchmarks and utilize these metrics for ongoing assessment and improvement of your robotics solutions.

Choose a specific challenge, outline the steps you took to diagnose the issue, and describe the solution you implemented. Highlight the skills and knowledge you applied, and what this experience taught you about problem-solving in robotics.

Share your strategies for continuous learning, such as following relevant research papers, attending webinars, joining technical forums or communities, and engaging in hands-on projects. Discuss specific resources that you find particularly valuable.

Talk about the tools and practices that facilitate communication and collaboration in a remote setup. Mention how you ensure alignment with team goals and how you maintain a sense of camaraderie despite the physical distance.

Reflect on the ongoing trends and potential future advancements in AI that will influence robotics. Discuss the transformative effects of combining AI with physical systems and how this can enable new capabilities in various industries.