25 of 25 Machine Learning Jobs in Cambridge

Title: Machine Learning Engineer (Computer Vision) Location: Cambridge Salary: Up to £160,000 (DOE) We are looking for a Machine Learning Engineer with experience in Computer Vision to join a growing engineering team developing machine learning solutions for complex real-world environments. This role … engineers, data scientists, and domain experts. The Role You will be responsible for designing, training, and deploying computer vision models, working across the full machine learning lifecycle. The work will involve building production-ready systems, evaluating model performance, and contributing to technical decisions across a range of projects. ...

role We re looking for AI Trainer Machine Learning Specialists to help train and evaluate cutting-edge AI models using real ML expertise. If you have the necessary experience, we ll send you a quick 10- to 15-minute test to assess your skills and suitability … though many are shorter. What you ll bring AI Training task skills and verifiable professional experience as a Machine Learning Specialist (e.g., ML engineer, data scientist, applied scientist, research engineer) A willingness to take our skills verification test to assess your suitability for our participant pool Strong attention ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 – AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 – Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems … Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 – Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 – Machine ...

across large codebases, contributing to CI/CD infrastructure, and shaping technical direction through thoughtful design and mentoring in a technically demanding environment spanning ML frameworks, infrastructure, and AI accelerator hardware. The Team The ML QA team is composed of highly skilled software engineers with a strong focus on automation … wider software organization. Operating in a fast-paced environment, the team plays a critical role in ensuring reliability, performance, and maintainability across the ML software stack, helping to deliver robust and high-quality products to customers. Responsibilities and Duties Design, implement, and maintain robust test infrastructure and automation ...

## Machine Learning Integration EngineerApplylocations: Cambridge Office, United Kingdomtime type: Full timeposted on: Posted Todayjob requisition id: JR101685Darktrace is a global leader in AI for cybersecurity that keeps organizations ahead of the changing threat landscape every day. Founded in 2013, Darktrace provides the essential cybersecurity platform protecting nearly … that requires attendance in the Cambridge office at least 2 days a week.**What will I be doing:**As a Software Engineer focussing on ML integration, you will assist with the deployment and optimisation of new and innovative machine learning models to further improve Darktrace’s services ...

optimisation, and production deployment of our next-generation foundation model. This is a deeply technical, hands-on role where you'll architect large-scale ML systems, optimise distributed training and inference, build GPU-accelerated infrastructure, and work directly with founders to solve complex engineering challenges. If you're excited … Foundation Model Development; Lead the research, development, and deployment of large-scale foundation models Define long-term technical strategy for high-performance ML systems Build scalable training and inference infrastructure Own model quality, performance, and reliability ML Infrastructure & Optimisation; Optimise distributed training and inference pipelines Design GPU-accelerated systems, including ...

Processing Engineer/Deep Learning Engineer/Optical Systems Engineer/Tracking Algorithm Specialist/Sensor Integration Engineer/R&D Engineer/ML Engineer/Algorithm Developer/Vision Software Engineer/Embedded Vision Engineer/Object Detection/Kalman Filter/Python/Blob Detection/Optical … Components/AI/ML/CV Development Engineer/AI Software Engineer/Machine Learning Engineer/Computer Vision Engineer/AI Research Engineer/ML Research Engineer/Computer Vision Software Developer ...

practical experience in applied AI or machine learning Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.) Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into production Solid understanding of cloud technologies, containerisation … building scalable AI applications Ability to integrate AI/ML models into real-world applications, focusing on usability and performance Strong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environment Experience working with large datasets, particularly in relation to demand and supply forecasting ...

when needed. Experience with hardware devices or sensors. Any experience with embedded systems, mobile OS or computer networking would be beneficial. Experience with deep-learning frameworks (TensorFlow or PyTorch) would be desirable. Exposure to computational statistics, algorithm development or machine learning optimisation would be a bonus. … develop your skills and knowledge with like-minded engineers. Keywords: Python, PyTorch, TensorFlow, Sensors, Embedded Systems, Hardware Interface, Mobile OS, Algorithms, Statistics, Machine Learning, Defence, Security Clearance, Start Up Another top job from ECM, the high-tech recruitment experts. Even if this job's not quite right ...

other engineers to develop sensing and imaging terahertz solutions. As a Backend Software Engineer you'll work on complex problems including image processing, machine learning, numerical simulation, user interfaces, databases, networking and interfacing with hardware. You'll be using a Python based tech stack but with constantly evolving … have experience with embedded software and/or IoT You are comfortable in an R&D environment You have an interest and understanding of Machine Learning and AI You are degree educated in a relevant STEM discipline You're collaborative, comfortable with Pair Programming and mentoring more junior ...

features. Who We're Looking For We're looking for a curious, analytical, and enthusiastic graduate who enjoys solving problems and learning new technologies. You'll be proactive, organised, and eager to develop your technical skills while working collaboratively in a supportive team environment. Requirements Essential Bachelor's degree … Google Gemini. Familiarity with Microsoft Excel or Google Sheets for handling data. Basic programming knowledge in Python, SQL, or JavaScript. Understanding of AI, machine learning, prompt engineering, or data analysis through university coursework or personal projects. Previous internship, placement, or personal projects related to AI or technology. Familiarity ...

code workflows, and intelligent document processing solutions. Lead the investigation and evaluation of AI technologies that can enhance regulatory processes, including NLP, machine learning, generative AI, and predictive analytics. Develop AI‐enabled use cases such as automated document classification, impact assessments, regulatory intelligence scanning, and predictive submission planning. … Receive United Kingdom: Competitive salary, annual bonus, pension scheme, health insurance, 24 days annual leave, flexible working arrangements, employee recognition scheme, and learning and development opportunities. Netherlands: Temporary employment for 1 year with a probation period and flexible working; learning and development opportunities; indefinite employment contract based ...

Technical Enablement Lead/Developer Relations Lead for the EU. The ideal candidate should have expertise in customer and field enablement, adult learning principles, educational program creation, use case architecture and implementation, and a genuine passion for Data and AI technologies. The candidate should be driven by a desire … champion product and process changes that make this a reality. You will work to understand the needs of different user personas (data scientists, machine learning engineers, scientists and R&D IT analysts), analyze their data environment, assist in the design and implementation of self-service solutions, and create ...

science environment (ideally biotech or applied life sciences). Strong application experience in data science methodologies including signal processing, classical algorithms, and machine learning. Ability to make sense of data within project context and company goals, so that insight can aid further research and projects. Good Python programming skills … awareness to write appropriate tests. Excellent communication skills with the ability to talk to non-technical and non-scientific stakeholders. Any exposure to training ML models (neural networks) would be desirable. This role would predominately be based at offices in Cambridge (although some flexibility for hybrid working would be possible ...

Learning Engineer (Foundation Models) to lead the development, optimisation, and production deployment of a next-generation foundation model. You will architect large-scale ML systems, optimise training and inference, and build GPU-accelerated infrastructure in collaboration with the founders. This deeply technical role demands hands-on expertise in Python … CUDA C/C++, PyTorch, and distributed ML pipelines, with onsite visits to London as #J-18808-Ljbffr ...

experience operating reliable, scalable production systemsNice to HaveExposure to AWS, Azure, or GCPFamiliarity with CI/CD or Git-based workflowsExperience with AI/ML or agent-based tooling in operationsUnderstanding of identity, access control, and security best practicesExperience with OpenStack (Cinder, Manila)Awareness of ITIL or service management frameworks ...

what you're building. \n You'll be part of a small cross-functional team (a Tech Lead plus four to six Software and Machine Learning Engineers), and you'll regularly run projects in parallel: contributing to ongoing experiments while also exploring entirely new directions. The tech stack … deliberately varied, the right tool for the job, not a fixed list, spanning C#, TypeScript, Python, and more across desktop, web, API, database, and ML development. \n What makes this role different: \n \n You'll work on problems where there is no established answer and you'll have ...

systems. Experience with GPU optimisation, performance modeling, and the simulation of large‐scale infrastructure workloads. Desirable Experience managing cross‐functional teams in AI infrastructure, ML systems, or computer architecture. Familiarity with Agile or other modern technical project management frameworks. Knowledge of modern inference‐serving frameworks (e.g., vLLM). Background ...

Windows development background Nice to have: real-time systems, networking or low-level programming, Python or C#, hardware/driver interfacing, and exposure to machine learning on sensor data. A BSc in a relevant field (or equivalent hands-on experience) rounds things off. You'll join a small ...

languages they require, instead they seek versatile candidates with strong knowledge of at least one programming language. Areas you could be involved with include ML systems, signal processing and software defined radio. The platforms you work on will vary from the cloud down to small low-power electronics and anything ...

Software Roots: A strong foundational background in embedded software is required, alongside the technical breadth to converse fluently across DSP, FPGA, and AI/ML domains. Proven Formal Management: Direct experience acting as a formal line manager for a team, handling appraisals and performance development. Experience managing other managers ...

prioritisation) Omni-channel decisioning (real-time & outbound) Decision governance, explainability, regulatory awareness Strong stakeholder management & Agile delivery Lead NBA Data Scientist Design and optimise ML models driving NBA decisioning. Key Skills: Pega CDH adaptive models Strong MLB/RTIM/arbitration logic knowledge Advanced Python & ML development A/… people with a supportive culture, rooted in our values and driven by our purpose. Promoting a culture of inclusion, collaboration, well-being, and learning and development. Providing increased agility and flexibility within our hybrid working model Investing in employees growth through ongoing training and development Autonomy to take ownership ...

signals into actionable compound discovery and optimisation, powering a pipeline across: Discovery → Prediction → Design → Validation We are looking for a Senior Computational Biologist with ML Engineering background to help build, bridge, and functionalise the link between AI-powered biological discovery and real-world clinical outcomes. This role sits across biological … discovery and scalable ML engineering. You will own key parts of the end-to-end architecture from data to model to evaluation to deployment, and work closely with ML engineers and software engineers to productise the platform into client-ready outputs. This is a senior role with significant autonomy ...

related research experience in academia or industry We will consider various levels of experience in relevant research areas Key Skills: Experience with ML frameworks (PyTorch, TensorFlow, JAX) and efficient ML (incl. quantization, pruning, sparsification, distillation, etc.) Experience with deployment on embedded/mobile devices (such as smartphones, with mobile ...