Nottingham, Nottinghamshire, United Kingdom Hybrid / WFH Options
Nexgencloud
Kubernetes management. Technical Competence: Ability to interpret logs and debug issues via command-line tools and scripts alongside other troubleshooting methods. GPU: understanding of utilisation and troubleshooting methods for Nvidia based GPU's Soft Skills: Strong detail orientated communication skills tailored to diverse audiences. Customer-focused problem-solving and support abilities with a focus on quality of interaction/experience. More ❯
impactful environment. Key Responsibilities: Design and develop high-performance C++ and Python code Port and optimise deep learning models for deployment on edge devices Work with tools such as Nvidia DeepStream and Triton Inference Server Collaborate with international teams including software developers and AI researchers. Essential Skills & Experience: Degree in Computer Science or a related field. Strong experience in modern More ❯
ROS, including advanced OpenCV, Boost, Standard library, and Jsoncpp for efficient data processing and manipulation. Implement machine learning models for object detection, particularly using YOLOv5, and optimize performance using Nvidia CUDA hardware acceleration. Develop, test, and deploy cloud-based applications and simulations, using Azure DevOps, Docker, and cloud-based agents for continuous integration and deployment. Write and maintain unit tests More ❯
Crawley, Sussex, United Kingdom Hybrid / WFH Options
Elekta AB
define infrastructure strategies that are scalable and meet the needs of the business. Design deployment architectures for high availability, performance, and cost-efficiency across on-premise (e.g., HP, Intel, Nvidia) and cloud platforms (e.g., Azure, AWS)." Evaluate and recommend hardware, software, and networking solutions, including virtualization strategies (e.g., Hyper-V, Kubernetes, VMware). Manage relationships with hardware and software More ❯
Lancaster, Lancashire, United Kingdom Hybrid / WFH Options
Galaxy Systems
or other LLMs integrated with document retrieval systems. Develop production-ready ML applications in cloud environments (AWS, SageMaker, Databricks, etc.). Leverage GPU-based computing resources and CUDA/Nvidia for performance optimization in training and inference. Collaborate with data engineers, software developers, and product teams to deliver AI/ML capabilities in production. Conduct rigorous model evaluations, A/… based models. Practical knowledge of LLM integration (e.g., GPT, Claude) and RAG architecture. Experience with ML lifecycle management tools like AWS SageMaker, MLflow, or Databricks. Working knowledge of CUDA, Nvidia GPUs, and distributed training. Experience with AWS services (S3, Lambda, EC2, SageMaker, Bedrock, etc.). Desired: Experience deploying models as APIs/microservices in cloud-native environments. Familiarity with prompt More ❯
