At a Glance
- Tasks: Build and operate multimodal pipelines for robotics datasets, ensuring quality and usability.
- Company: Join Miraxis, a pioneering company in robotics and physical AI data solutions.
- Benefits: Remote-friendly role with high ownership and opportunities for travel.
- Other info: Collaborate with a dynamic team and contribute to innovative projects.
- Why this job: Make a real impact in robotics by transforming messy data into training-ready datasets.
- Qualifications: Experience with robotics datasets and strong Python skills are essential.
The predicted salary is between 50000 - 70000 £ per year.
Miraxis is building the rights-cleared data factory for robotics and physical AI. A key differentiator is turning messy, heterogeneous real-world robotics data into training-ready datasets with verifiable quality. As Robotics Data Pipeline Engineer, you will own the multimodal pipeline layer: ingestion, transformation, validation, QA gates, and delivery packaging. You should be able to talk shop with vendors/partners/clients on best practices (formats, sync, calibration metadata, labeling, eval outputs) and also build the tooling to manipulate and audit datasets directly.
What you’ll do (Responsibilities)
- Build and operate multimodal pipelines for robotics/physical AI datasets: ingestion, transformation, validation, and delivery packaging.
- Define “training-ready” as enforceable checks: alignment validation, integrity checks, schema enforcement, and reproducibility standards.
- Build tooling to inspect, transform, and audit datasets (large files, long-running jobs, real-world edge cases).
- Collaborate with Ops/Delivery and Hardware & Integration to ensure capture metadata and formats support downstream usability.
- Work with partners/vendors/clients to align on formats and best practices; turn external constraints into concrete pipeline requirements.
- Maintain clear documentation (schemas, runbooks, data contracts) so a remote team can operate consistently.
What we’re looking for
- Hands-on experience with robotics/physical AI datasets (multimodal: video + sensors + proprioception) and their failure modes.
- Strong Python and data engineering instincts: validation, reproducibility, and careful handling of messy real-world data.
- Comfort working at the intersection of software and domain: can reason about timing/sync, calibration metadata, and the practicalities of capture pipelines.
- Able to communicate clearly with both engineers and external stakeholders; converts ambiguity into executable specs.
Nice to have
- Experience with ROS/ROS2 data formats (bags) or other robotics logging systems.
- Familiarity with simulation/teleoperation datasets, annotation/labeling workflows, and evaluation harnesses.
- Experience building QA frameworks that surface issues early (before downstream training).
Working style & expectations
- Remote-friendly, high-ownership role.
- Writing and maintaining clear docs is part of the job.
- Travel may be required occasionally for partner debugging and alignment.
Location
- Remote-friendly.
Robotics Data Pipeline Engineer in Portsmouth employer: Miraxis AI
Miraxis is an exceptional employer for those passionate about robotics and physical AI, offering a remote-friendly work environment that fosters high ownership and collaboration. Employees benefit from a culture of innovation, with opportunities for professional growth through hands-on experience with cutting-edge technology and direct engagement with industry partners. The company's commitment to clear documentation and best practices ensures that team members can thrive in their roles while contributing to meaningful projects that shape the future of robotics data.
StudySmarter Expert Advice🤫
We think this is how you could land Robotics Data Pipeline Engineer in Portsmouth
✨Tip Number 1
Network like a pro! Reach out to folks in the robotics and AI space on LinkedIn or at industry events. We can’t stress enough how important it is to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with multimodal pipelines and data handling. We love seeing real-world examples of how you’ve tackled messy data and built effective solutions.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and data engineering knowledge. We want to see how you think through problems, so practice explaining your thought process clearly and confidently.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who are ready to dive into the world of robotics and AI.
We think you need these skills to ace Robotics Data Pipeline Engineer in Portsmouth
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Robotics Data Pipeline Engineer role. Highlight your hands-on experience with robotics datasets and your Python skills. We want to see how your background aligns with our mission at Miraxis!
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work that showcase your ability to handle messy data, build pipelines, and collaborate with teams. We love seeing real-world applications of your expertise.
Keep It Clear and Concise:When writing your application, clarity is key. Use straightforward language and avoid jargon unless it’s relevant to the role. We appreciate well-structured documents that are easy to read and understand, especially since documentation is part of the job!
Apply Through Our Website:We encourage you to apply directly through our website. This way, your application goes straight to us, and we can review it promptly. Plus, it shows you’re keen on joining our team at Miraxis!
How to prepare for a job interview at Miraxis AI
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of robotics and physical AI datasets. Be ready to discuss specific examples of ingestion, transformation, and validation processes you've worked on. This will show that you can handle messy data and understand its failure modes.
✨Brush Up on Python Skills
Since strong Python skills are crucial for this role, practice coding problems related to data engineering. Be prepared to demonstrate your ability to write clean, efficient code that handles large datasets and implements validation checks.
✨Communicate Like a Pro
You’ll need to talk shop with various stakeholders, so practice explaining complex concepts in simple terms. Think about how you can convert technical jargon into clear, executable specs that everyone can understand.
✨Document Everything
Get into the habit of maintaining clear documentation. During the interview, mention how you’ve created schemas, runbooks, or data contracts in past projects. This shows you value consistency and can help a remote team operate smoothly.
