About Us
At Neuracore, we're building the world's first robot learning cloud service. Our platform eliminates the complexity of traditional robotics development by providing a complete end-to-end solution for data collection, model training, and deployment that works across different robot types and configurations.
Our multidisciplinary team is at the forefront of making robot learning accessible to organisations worldwide, from manufacturing and logistics to healthcare and research institutions. We're transforming how robotics teams develop, train, and deploy intelligent systems by providing cloud-native infrastructure that scales from small research projects to enterprise-wide robot fleets.
About the Role
Research Engineers at Neuracore work at the intersection of cutting-edge robotics research and scalable cloud infrastructure. You'll be responsible for developing and advancing the core algorithms, data processing pipelines, and learning methodologies that power our platform. This role combines deep technical research with practical implementation to solve real-world robotics challenges at scale.
As a Research Engineer, you'll work closely with our engineering team to translate the latest advances in robot learning into production-ready features that serve thousands of users across diverse industries and robot platforms.
Key Responsibilities:
* Algorithm Development: Research, implement, and optimize imitation learning and reinforcement learning algorithms for multi-embodiment robot systems
* Data Pipeline Innovation: Design and build scalable data processing systems that can handle diverse sensor modalities and robot configurations without traditional synchronization requirements
* Cross-Platform Integration: Develop and maintain APIs and interfaces that enable seamless data collection and model deployment across different robot platforms and manufacturers
* Foundation Model Research: Contribute to the development and improvement of our robot foundation models that can bootstrap learning across different robot types
* Performance Optimisation: Design efficient training pipelines that leverage multi-GPU infrastructure and intelligent resource allocation
* Research Translation: Transform cutting-edge research from top-tier conferences into production features that benefit our entire user base
* Experimentation Framework: Build tools and methodologies for large-scale experimentation and evaluation of robot learning approaches
About You
Required Skills and Experience:
* PhD or Master's degree in Computer Science, Robotics, Machine Learning, or related field
* Strong publication record in robot learning, with contributions at venues like CoRL, ICRA, RSS, ICML, ICLR, NeurIPS, CVPR, or IROS
* Deep expertise in machine learning frameworks (PyTorch, TensorFlow) with experience in distributed training
* Proven experience with reinforcement learning and/or imitation learning in robotics applications
* Strong software engineering skills with experience in building scalable systems
* Experience with cloud computing platforms and containerization technologies
Advantageous Skills and Experience:
* Experience with multi-robot systems and cross-embodiment learning
* Knowledge of modern MLOps practices and experiment tracking systems
* Background in computer vision and sensor fusion for robotics
* Experience with real-world robot data collection and deployment
* Knowledge of distributed systems and microservices architecture
* Experience with ROS/ROS2 and robot middleware systems
* Understanding of robotics simulation environments
* Track record of translating research into production systems
Join us in building the infrastructure that will accelerate robotics development worldwide and help bring intelligent robots into every industry.