126 to 150 of 1,499 Permanent Machine Learning Jobs

quality journalism. The department consists of four teams: Data Science & Engineering, Data Intelligence & Monetisation, Research & Insight and Customer Marketing. About You An accomplished ML/Data Engineer with proven experience deploying and managing ML and AI based services in production. Strong SQL skills and hands-on experience with both relational … Agentic workflows to build and deploy models agents and coding pipelines. Ideally having experience in Gemini, Claude and Vertex AI. Exposure to ML Frameworks such as PyTorch or TensorFlow. Agent orchestration using frameworks such as Langgraph or CrewAI Understanding of ML Ops such as automated model, testing,monitoring and tuning. ...

across oncology, immunology, and rare diseases. Backed by top-tier investors and leading scientific advisors, we’ve recently secured major funding to expand our ML platform and research capabilities globally. The Role We’re looking for a Machine Learning Team Lead to lead a high-performing team working … foundation models and probabilistic ML systems for drug discovery. You’ll sit at the intersection of research and engineering - driving technical direction, mentoring senior engineers and researchers, and helping scale both our platform and team as we push toward state-of-the-art biological modelling. This is a hands ...

intelligence to build practical, scalable solutions that deliver real business value.You'll collaborate with cross-functional teams to design, develop, and deploy data pipelines, machine learning models, and AI-enabled applications that support analytics, automation, and insight generation.This role suits someone who enjoys: Working with modern data … scalable data pipelines, datasets, and data models Support analytics, reporting, and AI-driven use cases Work with both structured and unstructured data sources AI & Machine Learning Develop and deploy machine learning models for: Prediction Classification Automation Insight generation Support the full life cycle from experimentation through ...

learning, and AI techniques to solve complex, real-world problems Research, design, and implement innovative models and solutions Work across the full ML lifecycle from requirements gathering and prototyping to deployment and live service support Deliver high-quality, scalable solutions with measurable impact Collaborate with multidisciplinary teams … Desirable Skills Experience working with text, audio, image, or video data Familiarity with cloud platforms (AWS, Azure, GCP) Strong Python skills and experience with ML libraries and frameworks (e.g. TensorFlow, PyTorch) Knowledge of statistics and probability Experience with ML lifecycle tools (e.g. MLflow, Kubeflow, Argo) Understanding of Ethical and Responsible ...

early-stage technology company looking for a Lead Data Scientist to play a key role in the development of its predictive modelling and machine learning capabilities. This is an opportunity to join at an early stage and have a significant influence on both the product and the direction … customer success and the future growth of the business. Skills and experience Experience building production machine learning models Strong Python and modern ML tooling experience A background in predictive modelling, classification, propensity modelling, churn prediction or related areas Excellent statistical and analytical thinking The ability to thrive ...

semantic search, recommendation, and knowledge graph-connected AI applications. This is not a conventional data science role. You will work at the intersection of machine learning, semantic data modelling, information retrieval, knowledge graphs, and real-world construction product data. Your work will help turn fragmented industry data into … reliable, contextual, and explainable decision intelligence. Responsibilities Develop machine learning and data science systems for classification, extraction, enrichment, matching, recommendation, and semantic search. Work with structured, semi-structured, unstructured, and graph-connected data. Build entity extraction, entity resolution, deduplication, and similarity-matching workflows. Connect AI outputs with taxonomy ...

innovation. They tackle some of the most complex business challenges across various domains, including customer experience, supply chain, marketing, and technology. By applying advanced machine learning techniques, generative AI, and large language models, they enhance pricing strategies, optimize store operations, and personalize customer interactions. This is a collaborative … environment where team members rotate across different domains, expanding their skills and impact. As a Data Scientist, you will: Develop and deploy machine learning solutions that enhance decision-making and improve customer service. Design and implement robust models while experimenting with new approaches.. This includes building data pipelines ...

will play a key part in enabling that shift, ensuring the data platform is structured in a way that supports more advanced analytics and machine learning use cases over time. Data is a critical, funded investment area for the business, with backing already in place and a clear … both regulatory and product needs. As the platform matures, you’ll also help enable more advanced capabilities, including predictive modelling, scenario optimisation, and machine learning use cases, ensuring the data foundations are built to support them properly. What You’ll Be Doing In the early stages ...

continuous improvement while enjoying a casual work environment and Great Place to Work culture! We are seeking a highly motivated and experienced Leader of ML and AI Engineering within the AI team. The ideal candidate will have a strong technical background in decision science, machine learning, and generative … lead the development of AI-powered solutions across different business areas. This involves understanding the business processes, identifying new opportunities to add value using ML/AI algorithms, and harnessing data sources to build state-of-the-art ML/AI solutions. Outcomes and Activities: This position will work from ...

applied machine learning solutions that power far-field voice experiences across connected devices and cloud platforms. Design, develop, train, and optimise scalable ML models for far-field voice detection, verification, and enhancement across device and cloud platforms. Contribute to innovation discussions and research in applied speech, audio signal … processing, ASR, NLP, and machine learning. Build cloud-based ML pipelines and APIs that process real-time audio streams at scale. Work closely with data scientists, audio engineers, product managers, and external partners to deliver robust and accurate voice experiences. Develop and document technical specifications, ensuring solutions meet latency ...

Environment (JTSE) and JLVC Modernization effort under the Joint Staff J7 (JS J 7) contract. This role focuses on developing advanced analytics, AI/ML models, and data architectures that enhance joint training, simulation, and decision support capabilities. What You Will Do • Lead end to end data science workflows, including … lifecycle monitoring. • Translate operational and training objectives into data driven solutions by defining analytical approaches and data requirements for integrating advanced AI/ML models into JTSE and Joint Training Tools. • Design and maintain scalable data pipelines and architectures that support real time and near real time ingestion, processing ...

that is actively investing in AI and moving from proof of concept into production. You will play a pivotal role in shaping how advanced ML and generative AI solutions are engineered, deployed and scaled, with genuine scope for the role to become permanent. The Company They are a large, well … focus on people, quality and long term outcomes. Data and AI are now a strategic priority, with senior backing to build robust, production grade ML capability. The Role Lead the engineering and productionisation of machine learning and generative AI solutions. Build and operate end to end ML pipelines ...

levels available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Manchester Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … look forward to hearing from you. KEY SKILLS: Data Science/Data Scientist/AI Engineer/AI/Machine Learning/ML/NLP/GenAI/Stakeholder Engagement/Customer Engagement/AWS/Azure/Cloud/Docker/Kubernetes/CI/CD/ ...

levels available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Cheltenham Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … look forward to hearing from you. KEY SKILLS: Data Science/Data Scientist/AI Engineer/AI/Machine Learning/ML/NLP/GenAI/Stakeholder Engagement/Customer Engagement/AWS/Azure/Cloud/Docker/Kubernetes/CI/CD/ ...

available £45k to £95k DoE plus 15% clearance bonus Must be willing to be full-time on-site in Central London Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy Who are we? We are recruiting Junior, Senior and Lead Data Scientists with AI specialism … look forward to hearing from you. KEY SKILLS: Data Science/Data Scientist/AI Engineer/AI/Machine Learning/ML/NLP/GenAI/Stakeholder Engagement/Customer Engagement/AWS/Azure/Cloud/Docker/Kubernetes/CI/CD/ ...

that is actively investing in AI and moving from proof of concept into production. You will play a pivotal role in shaping how advanced ML and generative AI solutions are engineered, deployed and scaled, with genuine scope for the role to become permanent. The Company They are a large, well … focus on people, quality and long term outcomes. Data and AI are now a strategic priority, with senior backing to build robust, production grade ML capability. The Role Lead the engineering and productionisation of machine learning and generative AI solutions. Build and operate end to end ML pipelines ...

influence the technical roadmap, and work directly with experienced founders and a senior engineering team. What you'll be doing: Designing, building and deploying ML-powered features across a production platform Working across Python and TypeScript, integrating models into scalable, real-time systems Fine-tuning and training NLP models using … best practices from the ground up Collaborating closely with product, engineering, and leadership What we're looking for: Strong commercial experience building and deploying ML models in production Proficiency in Python and familiarity with TypeScript/JavaScript Experience with NLP or recommendation systems is a bonus Excited by start ...

Principal Machine Learning Engineer to play a key role in shaping the architecture, strategy, and delivery of large-scale production ML systems powering live sports environments. This is a genuinely high-impact opportunity for someone who enjoys solving complex real-time engineering challenges while influencing technical direction across … platform teams. Key areas of focus include: Real-time sports insights & personalisation Computer vision & multimodal AI Live event detection & metadata generation Low-latency ML inference systems End-to-end MLOps & production ML Scalable cloud-native AI platforms What they’re looking for: Strong experience leading ML engineering initiatives in sports ...

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 ...

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 ...

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 ...

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 ...