5 of 5 Deep Learning Jobs in Cambridge

our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and Career Growth We're continuously … Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. BASIC QUALIFICATIONS - Deep experience in design/implementation/consulting experience of Machine Learning/AI/Deep Learning/Gen AI solutions - Strong understanding and experience in the … field of AI and related technologies, including deep learning and overall machine learning concepts. Deep experience developing AI models in real-world environments. - Strong understanding of Gen AI technologies. Having worked with both structured and unstructured data in the past to gain effective insights. - Solid grounding in statistics, probability theory, data modelling, machine learning algorithms More ❯

and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the project lifecycle. Possessing a deep understanding of AWS products and services, you will architect complex, scalable, and secure solutions tailored to meet each customer's needs. You'll gather requirements, assess current infrastructure, and … Data and AI/ML solutions and 8+ years defining long-term product/solution roadmaps with execution programs Hands-on experience with AI/ML workloads including machine learning, deep learning, NLP, CV, GNN, or distributed training Ability to create compelling customer proposals and present to executives; proficient English communication in technical and business settings Preferred More ❯

areas such as clean energy, personalised medicine, and climate science – and we need your help to create the tools, workflows, and community that will maximise its potential.This role combines deep technical work with the chance to help shape a growing national ecosystem of AI and HPC practitioners.What you’ll be doing Lead AI projects across a wide range of … enabling researchers to fully exploit advanced AI infrastructure. What we’re looking for Experience leading or mentoring technical specialists. Hands-on background in AI methods such as NLP, machine learning, deep learning, and statistical modelling (large language model experience a bonus). Proficiency in software engineering , with a strong grasp of algorithms and data structures. Excellent communication More ❯

Scientist, you will be expected to: Build Agentic AI and GenAI solutions, from PoC to production, using agile methodologies and best practices. Apply advanced analytical techniques, such as machine learning, natural language processing, computer vision, and deep learning, to extract insights and generate solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using … to data privacy regulations. Connect to your skills and professional experience A bachelor's degree (or equivalent) or higher in AI or equivalent. Proven experience in data science, machine learning, and AI, with a proven track record of delivering AI-driven solutions in a professional setting, using a variety of tools and techniques. Proficient in programming languages such as More ❯

GitHub Copilot for development. Ensure responsible AI practices aligned with NIST AI RMF , EU AI Act , and other ethical standards. Mentor junior developers and foster a culture of continuous learning and innovation. Skills & Experience 10+ years in software engineering, with strong experience building cloud-native or platform services using Microsoft and .NET . 4+ years in a Data Scientist … or AI/ML Engineer role. Proficiency in Python , including libraries like pandas , scikit-learn , TensorFlow , and PyTorch . Deep understanding of ML algorithms : regression, classification, clustering, and deep learning. Hands-on experience with Large Language Models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG) , agent orchestration , prompt engineering , and tool calling . Familiarity with AI standards More ❯