At a Glance
- Tasks: Build and operate multimodal data pipelines for robotics and AI datasets.
- Company: Join Miraxis, a pioneering company in robotics data solutions.
- Benefits: Remote-friendly role with high ownership and clear documentation expectations.
- Other info: Collaborate with engineers and external partners in a dynamic environment.
- 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 required.
The predicted salary is between 60000 - 80000 £ 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 Nottingham 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 multimodal data pipelines 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 advancements in the field.
StudySmarter Expert Advice🤫
We think this is how you could land Robotics Data Pipeline Engineer in Nottingham
✨Tip Number 1
Network like a pro! Reach out to folks in the robotics and AI space on LinkedIn or at industry events. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with multimodal pipelines or any relevant projects. We love seeing practical examples of your expertise, so don’t hold back!
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to data validation and pipeline management. We want to see how you think on your feet, so practice articulating your thought process clearly.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. 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 Nottingham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Robotics Data Pipeline Engineer role. Highlight your hands-on experience with robotics datasets and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Showcase Your Skills:In your cover letter, don't just list your skills—show us how you've used them in real-world scenarios. Talk about your experience with Python and data engineering, and how you've tackled messy data before. We love a good story!
Be Clear and Concise:When writing your application, keep it clear and to the point. Use straightforward language and avoid jargon unless it's relevant. We appreciate clarity, especially when it comes to technical details!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
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 intricacies.
✨Brush Up on Python Skills
Since strong Python skills are crucial for this role, practice coding problems related to data manipulation and validation. Be prepared to demonstrate your coding abilities during the interview, as it’s a great way to showcase your data engineering instincts.
✨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 anyone can understand. This will highlight your ability to bridge the gap between engineers and clients.
✨Prepare for Real-World Scenarios
Expect questions about real-world edge cases and how you would handle them. Think through potential failure modes of datasets and be ready to discuss how you would build QA frameworks to catch issues early. This shows you’re proactive and detail-oriented.
