1 to 25 of 36 Permanent Machine Learning Jobs in South Yorkshire

automotive market. As a Lead Data Scientist, you will take ownership of the AI (custom neural networks rather than third-party LLM technology) and machine learning capabilities behind products that influence high-value pricing and risk decisions. This is a hands-on technical leadership role where you will … with large, real-world datasets. Experience writing clean, maintainable, production-quality Python code. Experience with SQL for data analysis and data manipulation. Experience deploying ML workloads in cloud environments. Ability to independently own technical projects and make sound engineering decisions with minimal supervision. Strong problem-solving skills with the ability ...

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 ...

usability. 5+ years of engineering experience focused on Machine Learning, AI, and Data Science. Hands-on production experience with LLMs, PyTorch, ML pipelines, and modern prompt engineering frameworks. Strong skills in Python development, including building microservices and working with event-driven architectures. Proficiency in designing and consuming RESTful … GraphQL APIs. Experience with AWS or Azure ML services (e.g., SageMaker, Bedrock, Azure ML) and cloud-native development. Experience with PostgreSQL and MongoDB or similar relational and NoSQL databases. A solid grasp of system design, scalability, and performance optimization in ML-driven applications. A pragmatic, test-driven approach and experience ...

structure, experienced leaders and world-class benefits in place. More on working at Sona here. About the Role You'll join a two-person ML team that has built a production forecasting system running daily half-hourly predictions across multiple restaurant chains. Our forecasting models enter into a complex environment … perfect before moving on - the role requires pragmatism, parallelism, and iterative improvement Requirements You'll need these skills/experience to be successful: Production ML experience, with a track record of deploying ML systems that handle messy data, fail gracefully, and need monitoring Strong ML fundamentals - you can reason about ...

remote-sensing inputs to estimate site potential, forecast biomass and carbon trajectories, and quantify physical and permanence risk. Responsibilities: Design, train and evaluate ML models - from gradient-boosted methods to CNNs, U-Nets and vision transformers - for commodity and plantation mapping, land-cover classification, change and disturbance detection, and biomass … plots, and contribute to a strong research culture across Science, AI and Engineering - reviewed code, shared tooling, and active engagement with EO/ML literature. Who you are: Must-have requirements: Degree in a quantitative field: environmental/earth science, computer science, physics, maths, engineering, or similar. 3+ years ...

high-profile function and contribute to initiatives that enhance the efficiency, scalability, and effectiveness of the global workforce. The Opportunity Core Focus: Algorithm Design, Machine Learning/NLP, Statistical Rigor About the Role Once our 6 core datasets are unified, you will hold the keys to the mathematical … prediction drift, and safely surface model confidence scores to executive decision-makers. Required Technical Skills Experience: 24 years of experience as a Data Scientist, Machine Learning Engineer, or Quantitative Analyst. Exposure to recommendation algorithms, NLP, or People Analytics is a major plus. Python Mastery: Fluent in Python ...

high-profile function and contribute to initiatives that enhance the efficiency, scalability, and effectiveness of the global workforce. The Opportunity Core Focus: Algorithm Design, Machine Learning/NLP, Statistical Rigor About the Role Once our 6 core datasets are unified, you will hold the keys to the mathematical … prediction drift, and safely surface model confidence scores to executive decision-makers. Required Technical Skills Experience: 24 years of experience as a Data Scientist, Machine Learning Engineer, or Quantitative Analyst. Exposure to recommendation algorithms, NLP, or People Analytics is a major plus. Python Mastery: Fluent in Python ...

pace and become job-ready in as little as afew weeks. Our programme includes: Official AWS Certified Cloud Practitioner certification Training in Python, Machine Learning, and AI systems Hands-on projects using real-world AI tools and technologies Professional CV and LinkedIn support Interview preparation Dedicated recruitment support … cost of your training over 12 months so you can get qualified without financial pressure. Salary expectations: AI Engineer: £45,000 £60,000 Machine Learning Engineer: £60,000 £75,000 Progression into senior AI roles with higher earning potential We support you into employment We focus on outcomes ...

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 ...

models - you ll design the systems that make fraud detection possible. You ll work across modeling, data pipelines, and backend systems (Go) to ensure ML models run reliably, efficiently, and at scale. This is a chance to combine applied ML with large-scale systems engineering, owning end-to-end solutions … doing: Build and optimize data pipelines and backend services to process device and behavioral data in real time. Develop and deploy ML models for fraud detection, ensuring they run reliably and efficiently in production. Turn raw data into production-ready features that feed our fraud detection systems. Collaborate with platform ...

solutions. Typical engagements include: Engineering large-scale data ingestion and processing pipelines Designing data lakes and distributed data platforms Enabling analytics and AI/ML workloads Supporting intelligence data exploitation workflows Integrating multiple classified data sources across secure environments Job Responsibilities Design, build and maintain secure, scalable data platforms capable … Ensure data quality, reliability and performance through monitoring, validation and operational support mechanisms. Collaborate closely with data scientists to enable analytics and AI/ML workloads, including feature pipelines and data preparation processes. Optimise data storage and processing architectures to support high‐performance analytical environments. Contribute to DevSecOps and cloud ...

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 ...

resolution. 2. AI-Powered Virtual Agents & Automation Develop and optimize AI-driven virtual agents within Salesforce and external platforms. Utilize Einstein AI, NLP, and machine learning to enhance case deflection and automate customer support . Implement Conversational AI chatbots integrated with Live Chat, WhatsApp, and external messaging platforms … Channel Routing, and case automation . Familiarity with third-party AI, automation, and chatbot platforms outside Salesforce . Knowledge of API integrations, RPA, and machine learning-driven automation . Soft Skills & Experience Passionate about customer experience, AI, and digital transformation . Comfortable working directly with clients , understanding their ...

proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis. ...

with test integration in CI/CD environments (GitHub Actions, GitLab CI, Jenkins, or CircleCI) Experience using, integrating, or tutoring others with AI/ML or LLM-powered testing/coding solutions in Ruby projects. Familiarity with containerization technologies (Docker), automated deployment, and scripting within Ruby environments. Strong skills ...

enable our data driven approach, and: Support the building of robust data models downstream of backend services (mostly in BigQuery) that support internal reporting, machine learning as well as financial and regulatory use cases. Focus on optimisation of our Data Warehouse, spotting opportunities to reduce complexity and cost. … offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. Learning budget of £1,000 a year for books, training courses and conferences ➕And much more, see our full list of benefits here ...

Guide team best practices in Spark SQL usage, data documentation, and exploratory reproducibility. Desired Qualifications: 5+ years of experience in data science, applied analytics, machine learning, or analytical R&D. Advanced expertise in Python and distributed compute frameworks (e.g., Spark, Databricks), including strong proficiency in Spark SQL . ...

environment. Clear understanding of GDPR, FCA regulations, and secure data management. Strong collaboration, problem-solving, and communication skills. Desirable Skills: Experience with AI/ML integration for lead scoring or segmentation. Knowledge of Google Cloud, Azure, Docker, Kubernetes, or encrypted data pipelines. Familiarity with geolocation APIs like Ideal Postcodes. Benefits ...

development of AI-based systems that will redefine what s possible in sports Design, develop, and maintain scalable fullstack web applications integrating AI/ML models Collaborate on building PACETEQ s unified Sports Data Platform Implement backend services, RESTful APIs, and frontend UIs in modern JavaScript frameworks (React, or similar … Integrate ML models into production systems Help define software architecture that supports real-time decision intelligence for sports Contribute to DevOps and ML Ops pipelines. Learn and grow through cross-functional projects with a crew of embedded engineers, application developers, and sports experts Operate with speed and precision ...

secure solutions. \n Follow enterprise standards for security, governance, observability, and performance. \n Required Skills and Experience \n Strong experience in AI/ML engineering, with hands-on exposure to Generative AI use cases. \n Experience in building RAG applications in enterprise environments. \n Strong knowledge of document parsing ...

success. The day-to-day work is comprised of working on projects using cutting-edge technologies like RPA and connected technologies like machine learning, chatbots, and content intelligence tools like ABBYY, UiPath, Automation Anywhere, NICE, etc. both in-house and at our customer's offices (UK mostly NewCastle ...

Data+ certification and enables you to demonstrate your knowledge in advanced data processing, cleaning, and statistical modelling concepts. You will demonstrate your knowledge of machine learning, industry trends and use of specialised data science applications. You will also apply mathematical and statistical methods appropriately. Step ...

through to being qualified to work in a junior Data Scientist role. Through the interactive courses, you will gain knowledge in Python, R, Machine Learning, AI , and much more. You will also complete mini projects to gain practical experience and test your skills while you study. Step ...

communicate, and deliver upon project milestones with your team. Proactive growth mindset, always looking at ways to improve the status quo. Experience with building ML/AI-enabled products. Improve operational health, observability, and cost efficiency to keep systems scalable and sustainable. Demonstrated ability to help develop the technical mastery ...