Cambridge, England, United Kingdom Hybrid / WFH Options
Neutreeno
field Good foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, Hugging Face, vLLM, MCP, prompt engineering) Excellent communication skills and ability to explain ML concepts to non-technical stakeholders Ability to work effectively in multi-disciplinary teams, collaborating More ❯
cambridge, east anglia, united kingdom Hybrid / WFH Options
Neutreeno
field Good foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, Hugging Face, vLLM, MCP, prompt engineering) Excellent communication skills and ability to explain ML concepts to non-technical stakeholders Ability to work effectively in multi-disciplinary teams, collaborating More ❯
working with machine learning tools Ability to design, implement, and optimize solutions leveraging LLMs via API Experience using various LLMs (Open AI, Anthropic APIs) and AI Frameworks like langchain, Tensorflow etc. Hands-on experience testing AI-powered features (e.g., recommendation systems, computer vision models, chatbots). 2+ years of experience developing test plans and test cases Bachelor's degree More ❯
Cambridge, England, United Kingdom Hybrid / WFH Options
IC Resources
Computer Science, Machine Learning or related discipline 3+ years’ experience developing ML models, with a strong focus on medical imaging Proven track record using deep learning frameworks (PyTorch/TensorFlow) Solid Python skills and familiarity with cloud or MLOps tools (Docker, Kubernetes, MLFlow) Understanding of data pipelines and image analysis techniques (segmentation, registration, feature extraction) Benefits Share options and More ❯
cambridge, east anglia, united kingdom Hybrid / WFH Options
IC Resources
Computer Science, Machine Learning or related discipline 3+ years’ experience developing ML models, with a strong focus on medical imaging Proven track record using deep learning frameworks (PyTorch/TensorFlow) Solid Python skills and familiarity with cloud or MLOps tools (Docker, Kubernetes, MLFlow) Understanding of data pipelines and image analysis techniques (segmentation, registration, feature extraction) Benefits Share options and More ❯
Cambridge, Cambridgeshire, United Kingdom Hybrid / WFH Options
NLP PEOPLE
basic knowledge of hardware and software design. Experience developing and working with large software systems, especially in Python. Knowledge of state-of-the-art deep learning libraries such as TensorFlow and PyTorch. Experience training large deep learning models on GPU-based systems. Nice To Have Skills and Experience: ML Model Optimization techniques targeted for resource-constrained ARM edge compute More ❯
R&D Engineer - Camera Algorithm/Computer Vision | Cambridge | Telecommunications In this role, you will develop, optimize, and deploy advanced imaging algorithms for camera systems, contributing to high-performance, real-world applications. You will collaborate with cross-functional teams, including More ❯
R&D Engineer - Camera Algorithm/Computer Vision | Cambridge | Telecommunications In this role, you will develop, optimize, and deploy advanced imaging algorithms for camera systems, contributing to high-performance, real-world applications. You will collaborate with cross-functional teams, including More ❯
We’re Looking For Ph.D. or Master’s degree in Computer Science, Machine Learning, Information or Biomedical Engineering (or similar). Strong experience with deep learning frameworks (PyTorch/TensorFlow) and Python development. Proven background in on-device ML (TinyML) using frameworks such as TensorFlow Lite, ExecuTorch, or TVM. Solid understanding of model optimisation for constrained hardware environments. More ❯
We’re Looking For Ph.D. or Master’s degree in Computer Science, Machine Learning, Information or Biomedical Engineering (or similar). Strong experience with deep learning frameworks (PyTorch/TensorFlow) and Python development. Proven background in on-device ML (TinyML) using frameworks such as TensorFlow Lite, ExecuTorch, or TVM. Solid understanding of model optimisation for constrained hardware environments. More ❯
