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For Companies At a Glance
- Tasks: Implement cutting-edge AI systems for robotics and translate research into production.
- Company: Join a stealth-mode London startup revolutionising industrial robotics with generative AI.
- Benefits: Work on innovative projects, collaborate with experts, and enjoy a dynamic startup culture.
- Why this job: Be at the forefront of robotics innovation and make a real impact across industries.
- Qualifications: Advanced degree in Computer Science, Robotics, or related field; strong ML expertise required.
- Other info: Experience with cloud platforms and robotics middleware is a plus.
The predicted salary is between 48000 - 72000 £ per year.
Please note: This is an external role with one of our valued customers, not a direct position with our company.
About the Company
The Company is a London-based startup currently in stealth mode which is pioneering the application of generative AI to industrial robotics. The Company is developing its own generative AI models along with an integrated platform and related tools to unlock intelligent automation using existing, proven robotic hardware. The Company's mission is to radically expand what robots can do in industrial and commercial environments, making automation more accessible, flexible, and impactful across multiple industries.
About the Role
The company is seeking a Machine Learning Engineer to implement and integrate cutting-edge AI systems for robotics applications. You will research and implement advanced learning algorithms, build scalable data pipelines, and translate breakthrough research into production systems. This role offers the opportunity to work on foundation models for robotics, multi-embodiment learning, and the infrastructure that will accelerate robotics development across industries.
Key Responsibilities
- Translate research to production by implementing state-of-the-art algorithms from top-tier conferences into deployed systems.
- Train deep learning models that handle multi-modal sensor data from different robot configurations and manufacturers.
- Collaborate with senior scientists to refine existing algorithms, suggesting improvements to maximise success rate on target applications.
- Utilise existing training infrastructure leveraging multi-GPU systems and distributed computing for large-scale model training.
- Create experimentation frameworks for large-scale evaluation and testing of robot learning approaches.
Required Skills
- Advanced degree (PhD, Master's, or equivalent experience) in Computer Science, Robotics, Machine Learning, or related field.
- Strong research background with publications at venues like CoRL, ICRA, RSS, ICML, ICLR, NeurIPS, or similar.
- Deep ML expertise in PyTorch or TensorFlow with experience in distributed training and optimisation.
- Robotics learning experience with practical knowledge of reinforcement learning and/or imitation learning.
- Production software skills with ability to build scalable, maintainable systems beyond research prototypes.
- Cloud infrastructure experience with platforms like AWS, GCP, or Azure and containerisation technologies.
Preferred Skills
- Multi-robot systems experience and cross-embodiment learning approaches.
- MLOps expertise including experiment tracking, model versioning, and deployment pipelines.
- Computer vision and sensor fusion for robotics applications.
- Real-world deployment experience with robot data collection and production model serving.
- Robotics middleware experience with ROS/ROS2 or similar frameworks.
- Familiarity with simulation environments and synthetic data generation.
Machine Learning Engineer: Robotics employer: Neuraco
Contact Detail:
Neuraco Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer: Robotics
✨Tip Number 1
Familiarise yourself with the latest research in generative AI and robotics. Follow key conferences like NeurIPS and ICRA to stay updated on cutting-edge algorithms that you might be implementing in this role.
✨Tip Number 2
Network with professionals in the field of machine learning and robotics. Attend meetups or webinars where you can connect with experts and potentially get insights into the company’s culture and expectations.
✨Tip Number 3
Showcase your practical experience with distributed training and optimisation in your discussions. Be prepared to discuss specific projects where you've successfully implemented these techniques, as they are crucial for this role.
✨Tip Number 4
Demonstrate your understanding of MLOps practices. Be ready to talk about how you've managed experiment tracking, model versioning, and deployment pipelines in previous roles, as this will be highly relevant to the position.
We think you need these skills to ace Machine Learning Engineer: Robotics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, robotics, and any specific projects that align with the job description. Emphasise your advanced degree and any publications in top-tier conferences.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for generative AI and robotics. Mention specific skills like your expertise in PyTorch or TensorFlow, and how they relate to the role. Be sure to express your enthusiasm for the company's mission.
Showcase Relevant Projects: Include a section in your application that details any relevant projects you've worked on, especially those involving multi-modal sensor data, reinforcement learning, or cloud infrastructure. This will demonstrate your practical experience and problem-solving skills.
Proofread and Edit: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application reflects your attention to detail and professionalism, which are crucial in technical roles.
How to prepare for a job interview at Neuraco
✨Showcase Your Research Background
Make sure to highlight your research experience, especially any publications in top-tier conferences like NeurIPS or ICML. Be prepared to discuss your contributions and how they relate to the role, as this will demonstrate your depth of knowledge in machine learning and robotics.
✨Demonstrate Technical Proficiency
Familiarise yourself with the tools and frameworks mentioned in the job description, such as PyTorch, TensorFlow, and cloud platforms like AWS or GCP. Be ready to discuss specific projects where you've used these technologies, showcasing your ability to build scalable systems.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving skills, particularly in reinforcement learning and multi-modal sensor data handling. Practice explaining your thought process clearly and concisely, as this will help interviewers gauge your analytical abilities.
✨Engage with the Company's Mission
Research the company's mission and values, especially their focus on generative AI in robotics. During the interview, express your enthusiasm for their goals and how your skills can contribute to making automation more accessible and impactful across industries.
