1 to 25 of 512 Permanent Machine Learning Jobs in the South East

role, you’ll help design, develop, and deploy machine learning models that solve real-world problems — all while receiving hands-on training, mentoring, and support from experienced ML engineers and data scientists. Whether you studied Computer Science, Engineering, Data Science, or Maths — if you're passionate about machine learning, love to build, and eager to learn … this is the perfect opportunity to kickstart your career. What You’ll Be Doing You’ll play a key role in helping our team develop and deliver ML-powered solutions: Model Development : Assist in building and training machine learning and deep learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work … and selection of relevant input features to improve model performance Model Evaluation : Learn to test models for accuracy, robustness, and fairness using best practices Deployment : Help package and deploy ML models into production using tools like Docker, APIs, or cloud platforms Collaboration : Work closely with software engineers, data scientists, and product teams to integrate ML into real products and services More ❯

models and AI systems. Collaborate extensively with scientific and operational teams to guarantee the robustness, scalability, and reliability of our AI tools. Implementing automation and standardization throughout the ML lifecycle, your efforts will support quicker, data-informed decision-making and boost innovation. Help our CDMO's mission by turning research insights into practical solutions efficiently. Key responsibilities: Compose, construct … successful deployment of machine learning and large language models (LLMs) in practical operational settings, transforming research findings into functional business tools. Facilitate the progress and examination of ML models, involving both standard machine learning and neural network-focused models, as requested by R&D teams. Develop standardized, reusable workflows that can be applied across different projects … on. Key requirements: MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

learning models and AI-driven solutions to address business challenges. Collaborate with data scientists to transition prototypes into production-ready systems . Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment. Optimise model performance, scalability, and reliability using MLOps best practices. Work with large-scale structured and unstructured datasets for model training and … validation. Implement model monitoring, versioning, and retraining processes to ensure continuous improvement. Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments. Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer … lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or More ❯

Head of AI & Machine Learning London (Hybrid - 2 days on-site) £180,000 base + equity + bonus The Opportunity I'm working with one of the UK's most exciting AI scale-ups, a forward-thinking business that's just secured a significant Series B funding round. They're building cutting-edge, applied AI technology that's … a pivotal role in setting the technical direction of the company. This role blends hands-on technical expertise with strategic leadership. You'll: Own and drive the AI/ML strategy across the organisation. Lead and scale a world-class team of data scientists and ML engineers. Guide research and development of advanced machine learning and generative AI … of the curve on emerging AI trends and represent them externally as a thought leader. What They're Looking For A proven leader with experience heading up AI/ML teams in a high-growth tech environment. Deep technical expertise across machine learning, deep learning, and ideally generative AI. Strong ability to combine strategy with execution, from More ❯

software, infrastructure, and MLOps systems that leverage machine learning. Working in cross-functional teams with engineers, data scientists, product managers, and designers. Developing scalable, reusable tools that accelerate ML delivery. Providing technical expertise to customers and mentoring junior engineers. Contributing to the scope, design, and technical delivery of complex projects. Embedding best practices for AI systems in production, balancing … and operational requirements. What we're looking for Active SC clearance(minimum 5 years UK residency required). Strong software engineering skills, with proficiency in Python. Experience across the ML lifecycle, including deploying models built in PyTorch, TensorFlow, or Scikit-learn. Hands-on cloud experience with AWS, Azure, or GCP. Knowledge of Docker and Kubernetes, with practical containerisation experience. Understanding … of probability, statistics, and ML techniques. Strong communication skills, able to engage with technical and non-technical stakeholders. Experience mentoring or leading junior engineers is an advantage. Travel & Location Open to applicants from anywhere in the UK. Travel to Poole or Hereford up to 2/3 days per week Majority of work can be done remotely. Why join Salary More ❯

edge machine learning capabilities. The Role You will join a collaborative Research and Development team based in Oxford, contributing to the development and maintenance of a modern ML operations stack. This includes data acquisition pipelines, data management, and machine learning model training infrastructure. The environment includes both self-managed on premise systems and cloud-based infrastructure … primarily using AWS. You will have the opportunity to influence the technical direction of the ML Ops team, propose new areas for development, and potentially lead your own projects. This is a hybrid role combining remote and on site working. There is no expectation to be available outside core business hours. Key Responsibilities Maintain and improve ML Ops infrastructure Manage … on premise Kubernetes clusters and ML pipelines Integrate ML toolkits into operational workflows Collaborate with ML developers to streamline workflows Suggest and implement technical improvements and new tools Required Skills and Experience Academic background (research Masters level) or industry experience in a relevant field Strong experience managing on premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as More ❯

/RemotePackage: Strong Salary + Benefits We're partnered with a fast-growing tech business that's investing heavily in its AI capability. They're looking for a proven ML/AI leader who can take charge of multiple high-performing teams and set the direction for how Machine Learning is built and scaled across the organisation. This … isn't about "experiments in the corner", it's about shaping strategy, leading delivery, and putting advanced ML systems into production where they make a measurable difference. What you'll be doing: Leading and scaling cross-functional teams (Data Science, ML Engineering, Software Engineering, Managers). Defining the ML/AI roadmap and aligning it to business outcomes. Driving best … practice in MLOps, deployment, observability, and automation. Working with cutting-edge approaches: deep learning frameworks, foundation models, knowledge graphs, etc. Being the voice of ML/AI leadership, setting standards, mentoring, and building a culture of delivery. What they're looking for: You've built and run ML teams at scale, and delivered systems into production, not just research. More ❯

in office) Up to £120,000 Shares + Benefits A fast-growing Data & AI Product-based company at the forefront of cutting-edge AI solutions are looking for an ML Lead to join the team and spearhead a number of ambitious products, shaping the architecture, direction, and delivery of advanced AI and Machine Learning initiatives. What youll do … Lead the design and development of Agentic AI systems, generative models, and NLP-powered solutions. Guide and manage a small talented ML engineering team, fostering innovation and technical excellence. Collaborate with product, data science, and engineering teams to bring state-of-the-art research into production. Evaluate and implement the latest AI frameworks, libraries, and cloud tools. Champion best practices … in model deployment, evaluation, and optimisation. What were looking for Strong track record in ML leadership, ideally in production-scale AI systems. Expertise in Agentic AI, LLM-based architectures, NLP techniques, and generative AI models. Solid programming skills (Python preferred) and experience with ML frameworks such as PyTorch, TensorFlow, Hugging Face. Hands-on experience with prompt engineering, fine-tuning LLMs More ❯

Learning Engineer to join their London Government team on a 6-month fixed-term contract . This role offers the opportunity to design, build, and deploy production-grade ML systems that have a direct impact on government services and policy delivery. What you'll be doing Designing and delivering software, infrastructure, and MLOps systems that bring ML models into … real-world use. Collaborating in cross-functional teams with engineers, data scientists, product managers, and designers. Creating scalable, reusable tools that improve ML deployment and operationalisation. Leading on technical design and delivery of government-focused projects. Providing technical expertise to stakeholders and mentoring less experienced engineers. Developing and embedding best practices for managing ML in production. What we're looking … for Active SC Clearance Strong software engineering background with proficiency in Python. Experience deploying ML models built with frameworks such as PyTorch, TensorFlow, or Scikit-learn. Knowledge of probability, statistics, and common ML techniques. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP). Proficiency with containers, Docker, and Kubernetes. Strong communication skills with the More ❯

machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure seamless integration of ML models into products. … Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration … with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure seamless integration of ML models into products. … Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration … with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

machine learning models for production use. Collaborate with data scientists to turn research prototypes into production-grade solutions. Build robust data pipelines and feature engineering workflows. Deploy ML solutions into cloud environments (AWS, GCP, or Azure). Implement monitoring, testing, and model performance evaluation frameworks. Work with engineering teams to ensure seamless integration of ML models into products. … Contribute to improving infrastructure, tooling, and best practices for ML development and deployment. Skills & Experience Essential: Strong programming skills in Python (and frameworks such as PyTorch, TensorFlow, or Scikit-learn). Proven experience in developing and deploying machine learning models in production. Solid understanding of data structures, algorithms, and software engineering principles. Experience with ML pipelines and orchestration … with NLP, computer vision, or time-series forecasting. Familiarity with distributed computing frameworks (Spark, Ray). Experience with MLOps and model governance practices. Previous contract experience in a similar ML engineering role. Contract Details Duration: 6–12 months (extension possible) Location: London (Hybrid working model) Day Rate: Competitive, depending on experience More ❯

practices in these areas is essential. Essential Skills: Proficient in Python programming (2+ years' experience) Previous experience in the development and use of Convolution Neural Networks (CNN's) for machine vision and image analysis applications Previous development and fast prototyping experience in at one of following specializations of computer vision or machine learning: Object/face/… tracking Activity Recgnition Camera Calibratin 3D stere, SLAM or Depth estimation from video Proficient in Linux Experience with Docker Experience with large-scale data sets Proficient with open source machine learning platforms such PyTorch or Keras/tensorflow. Ability to develop using rapid prototyping techniques aimed at demonstrating applications quickly in a fast moving environment. Agile/DevOps … Integration/Continuous Delivery practices. Good written and excellent spoken communication skills as well as attention to detail. Desired Skills: • MSc or PhD degree in Computer Science, Computer Vision, Machine Learning, Robotics or related technical field. Python experience Experience shipping computer vision solutions or fast prototyping and development Strong grasp of latest cutting edge research in object detection More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

Manage multiple projects from inception to deployment within cloud-based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world … Experience managing multiple end-to-end data science projects across varied data types. Familiarity with DevOps practices and tools like Git. Cloud experience (e.g. Azure, AWS) and working with ML platforms and services. Strong communication skills, capable of explaining complex topics to non-technical stakeholders. Ability to align data science efforts with broader business objectives. Desirable Skills: Experience using R … and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel, SQL, Power BI More ❯

Manage multiple projects from inception to deployment within cloud-based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world … Experience managing multiple end-to-end data science projects across varied data types. Familiarity with DevOps practices and tools like Git. Cloud experience (e.g. Azure, AWS) and working with ML platforms and services. Strong communication skills, capable of explaining complex topics to non-technical stakeholders. Ability to align data science efforts with broader business objectives. Desirable Skills: Experience using R … and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel, SQL, Power BI More ❯

Manage multiple projects from inception to deployment within cloud-based environments. Maintain high standards in code review, documentation, and delivery in a DevOps context. Apply a deep understanding of ML techniques, from supervised/unsupervised learning to generative AI and large language models. What We’re Looking For Essential Skills and Experience: Proven ability to solve complex, real-world … Experience managing multiple end-to-end data science projects across varied data types. Familiarity with DevOps practices and tools like Git. Cloud experience (e.g. Azure, AWS) and working with ML platforms and services. Strong communication skills, capable of explaining complex topics to non-technical stakeholders. Ability to align data science efforts with broader business objectives. Desirable Skills: Experience using R … and NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. Strong working knowledge of Excel, SQL, Power BI More ❯

programs. Align with our industry partners to develop your career and the solutions we deliver for our clients. In this role you will: Solve challenging business problems using advanced machine learning methods such as Deep Learning and quantitative analytics. Understand business requirements and support the development of business cases. Run discovery analytics to identify new and innovative … opportunities. Partner with developers and engineers to deploy machine learning algorithms to deliver business value. Define approaches to embed and scale machine learning models. Build reusable assets, solutions and develop best practices for current and future business problems. Consult on complex analyses and advanced machine learning methods. Communicate and provide guidance to senior client More ❯

Java Software Engineer - Java, Python, AWS, MySQL, NoSql, REST APIs, Microservices, Machine Learning, Artificial intelligence (Hybrid 3 days a week in the office) Java Software Engineer:- You will be joining a fast-growing, research-driven company building an artificial intelligence using novel machine learning techniques. My client is revolutionising their industry with a track record of … Technologies (AWS) and Microservices Strong Database experience Degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience in engineering. Experience or interest in AI or Machine Learning Salary for the Java Software Engineer will depend on experience, but expect between £60,000 and £80,000 + Pension + benefits Other benefits include:- Free breakfast … games etc.) The latest tech, generous annual leave and an amazing office with a balcony overlooking Notting Hill. Java Software Engineer - Java, Python, AWS, MySQL, NoSql, REST APIs, Microservices, Machine Learning, Artificial intelligence (Remote or Hybrid - You choose!) Applicants must have the right to work in the UK, no sponsorship is offered for this role More ❯

the other dedicated to fundamental research that supports both our applications and the broader scientific community. Current areas of interest include large language models (LLMs), optimization methods for deep learning, reinforcement learning (RL), and generative models. Responsibilities:- Contribute to ongoing research in machine learning and artificial intelligence Help develop and implement algorithms Collaborate with researchers and … in preparing publications and technical reports Stay up to date with the latest advancements in AI and related fields Requirement Qualifications Required: Currently enrolled in a PhD program in Machine Learning, Artificial Intelligence, Mathematics, Computer Science, Physics, or a related field Strong interest in research and a background in machine learning or a related area Experience … similar Strong problem-solving skills and ability to work independently and collaboratively Good communication skills and ability to present complex ideas clearly Nice-to-have Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Previous research publications or submitted papers Why Join Us Gain hands-on More ❯

the other dedicated to fundamental research that supports both our applications and the broader scientific community. Current areas of interest include large language models (LLMs), optimization methods for deep learning, reinforcement learning (RL), and generative models. Responsibilities:- Contribute to ongoing research in machine learning and artificial intelligence Help develop and implement algorithms Collaborate with researchers and … in preparing publications and technical reports Stay up to date with the latest advancements in AI and related fields Requirement Qualifications Required: Currently enrolled in a PhD program in Machine Learning, Artificial Intelligence, Mathematics, Computer Science, Physics, or a related field Strong interest in research and a background in machine learning or a related area Experience … similar Strong problem-solving skills and ability to work independently and collaboratively Good communication skills and ability to present complex ideas clearly Nice-to-have Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Previous research publications or submitted papers Why Join Us Gain hands-on More ❯