We're looking for a data scientist to deploy machine learning models on edge devices, wearables, and mobile robotics platforms. You'll optimise our models to run efficiently on resource-constrained hardware, focusing on minimal latency, reduced power consumption, and compact model architectures.
Key Responsibilities
Deploy and optimise machine learning models for embedded systems and edge devices
Implement efficient inference pipelines in Rust using any of the following Burn, Candle,tch‑rs, Rust‑BERT, nnl, rustorch, rustyml framework
Reduce model size and computational requirements through quantisation, pruning, and distillation
Minimise latency in real-time systems whilst maintaining model performance
Profile and optimise memory usage and power consumption for battery-powered devices
Collaborate with robotics engineers to integrate ML models into hardware platforms
Benchmark performance across different embedded processors and accelerators
Essential Requirements
Strong data science background with practical ML model development experience
Proficiency in Rust for systems programming and embedded applications
Strong Python proficiency enabling quick experimentation and prototyping.
Experience with any of: Burn, Candle, tch‑rs, Rust‑BERT, nnl, rustorch, rustyml or willingness to work extensively with Rust-native deep learning frameworks
Experience with model optimisation techniques (quantisation, pruning, knowledge distillation)
Understanding of embeddings and their efficient representation
Knowledge of edge ML frameworks and deployment strategies
Experience with robotics platforms or embedded Linux systems
Understanding of hardware constraints (memory, compute, power)
Experience with cloud platforms such as Azure or AWS.
Desirable Skills
Experience with ARM processors, microcontrollers, or specialised ML accelerators
Knowledge of ROS (Robot Operating System) or similar robotics middleware
Familiarity with sensor fusion and real-time processing
Experience with wearable device development
Understanding of battery management and power-efficient computing
Contributions to Rust ML ecosystem or embedded Rust projects
Additional Information:
• This is a full-time position.
• We offer competitive salary packages and benefits.
• Professional growth and learning opportunities will be provided.
• A positive and collaborative work environment awaits you.
If you are passionate about contributing to the exciting field of generative AI and creating innovative applications that push the boundaries of technology, we would love to hear from you.
Apply now to embark on an exciting journey as an Embedded AI Data Scientist and be part of a cutting-edge research and development and creating exceptional digital experiences for our clients. Please submit your resume and portfolio showcasing your development work.
