1,401 to 1,425 of 4,245 Machine Learning Jobs in England

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

developed, deployed, and scaled across the organisation. This is a genuinely high-impact role: you’ll lead a talented team of 6-8 engineers, set the strategic direction for ML infrastructure, and ensure the business continues to deliver reliable, scalable, and high-performing ML systems that drive real-world impact. Key Responsibilities for Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million … high performance, and personal growth. Define and deliver the MLOps roadmap, aligning closely with the wider engineering and data strategy. Provide guidance on architecture, tooling, and best practices for ML pipelines, deployment, monitoring, and incident management. Partner with data science, ML, and product teams to ensure infrastructure supports innovation and business needs. Oversee system reliability, cost optimisation, and vendor relationships … to keep infrastructure scalable and efficient. Take ownership of critical ML/infra incidents, ensuring swift resolution and continuous learning. Deliver clear progress, risk, and priority updates to leadership in a concise and actionable way. Requirements for the role: Proven experience leading an MLOps, ML Engineering, or Platform Engineering team. Solid background in applied machine learning and a More ❯

House AI Environment Location: London, Bank (onsite) Type: Full-time | Permanent Salary: Competitive + Benefits About Us We’re an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker — but it’s time to take … make that happen, we’re looking for an AI Infrastructure Lead — someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem. You’ll … workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and NLP researchers to optimize infrastructure for experimentation. Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure. Lead future recruitment and mentoring of additional AI engineers. Requirements More ❯

House AI Environment Location: London, Bank (onsite) Type: Full-time | Permanent Salary: Competitive + Benefits About Us We’re an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker — but it’s time to take … make that happen, we’re looking for an AI Infrastructure Lead — someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem. You’ll … workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and NLP researchers to optimize infrastructure for experimentation. Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure. Lead future recruitment and mentoring of additional AI engineers. Requirements More ❯

House AI Environment Location: London, Bank (onsite) Type: Full-time Permanent Salary: Competitive + Benefits About Us We're an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker - but it's time to take … make that happen, we're looking for an AI Infrastructure Lead - someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you'll take ownership of designing and building the foundation of our AI ecosystem. You'll … workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and NLP researchers to optimize infrastructure for experimentation. Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure. Lead future recruitment and mentoring of additional AI engineers. Requirements More ❯

House AI Environment Location: London, Bank (onsite) Type: Full-time | Permanent Salary: Competitive + Benefits About Us We’re an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker — but it’s time to take … make that happen, we’re looking for an AI Infrastructure Lead — someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem. You’ll … workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and NLP researchers to optimize infrastructure for experimentation. Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure. Lead future recruitment and mentoring of additional AI engineers. Requirements More ❯

House AI Environment Location: London, Bank (onsite) Type: Full-time | Permanent Salary: Competitive + Benefits About Us We’re an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker — but it’s time to take … make that happen, we’re looking for an AI Infrastructure Lead — someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem. You’ll … workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and NLP researchers to optimize infrastructure for experimentation. Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure. Lead future recruitment and mentoring of additional AI engineers. Requirements More ❯

House AI Environment Location: London, Bank (onsite) Type: Full-time | Permanent Salary: Competitive + Benefits About Us We’re an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker — but it’s time to take … make that happen, we’re looking for an AI Infrastructure Lead — someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business. The Role As our first senior AI hire, you’ll take ownership of designing and building the foundation of our AI ecosystem. You’ll … workflows for training, deploying, and monitoring models. Integrate and manage containerized AI engines (Docker/Kubernetes). Establish best practices for model versioning, data pipelines, and reproducibility. Collaborate with ML and NLP researchers to optimize infrastructure for experimentation. Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure. Lead future recruitment and mentoring of additional AI engineers. Requirements More ❯

Data Scientist (LLMs & ML) - UK Remote A fast-growing healthcare organization is seeking a Data Scientist with strong experience in machine learning, deep learning, and Large Language Models (LLMs) to help drive innovation and automation in clinical services. This is a full-time, remote UK-based role. ***Unfortunately we can't consider candidates that require sponsorship*** Compensation … Develop and optimize predictive models using scikit-learn, PyTorch, TensorFlow, and XGBoost. Design robust data pipelines using tools like Spark and Kafka for real-time and batch processing. Manage ML lifecycle with tools such as Databricks , MLflow , and cloud-native platforms (Azure preferred). Collaborate with engineering teams to ensure scalable, secure ML infrastructure aligned with compliance standards (e.g., ISO27001 … . Ensure data governance, particularly around sensitive healthcare data. Share best practices and stay current with developments in AI, ML, and LLMs. Proven experience with LLM frameworks and transformer-based architectures. Strong Python skills and familiarity with key ML/DL libraries. Experience with Azure (or similar cloud platforms), containerization (Docker/Kubernetes a plus), and MLOps tools. Understanding of More ❯

day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won't find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your … will work in a multi-disciplinary team and build the firm's reputation in your area of expertise. You will ensure statistical validity and outputs of analytics, AI/ML models and translate results for senior stakeholders. You will write optimized code to advance our Data Science Toolbox and codify analytical methodologies for future deployment. You will be working in … python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision Ability to write production More ❯

Join a management consultancy that has been disrupting the industry for over a decade. They work across sectors including Defence, Retail, Government, and Healthcare, delivering bespoke Data Science and Machine Learning solutions. By combining strategy, innovation, and execution, they help organizations turn bold ideas into real-world impact Responsibilities: Own the end-to-end delivery of complex data … science and machine learning projects Define and drive data science strategies that align … with client goals and broader organizational objectives. Develop tailored models and algorithms to solve unique client problems to deliver real business value. Stay at the forefront of AI/ML trends and emerging technologies, identifying opportunities to apply new techniques and tools. Support business development by contributing to proposals, pitching solutions, and identifying new areas for consultancy services. Requirements: MSc More ❯

Join a management consultancy that has been disrupting the industry for over a decade. They work across sectors including Defence, Retail, Government, and Healthcare, delivering bespoke Data Science and Machine Learning solutions. By combining strategy, innovation, and execution, they help organizations turn bold ideas into real-world impact Responsibilities: Own the end-to-end delivery of complex data … science and machine learning projects Define and drive data science strategies that align … with client goals and broader organizational objectives. Develop tailored models and algorithms to solve unique client problems to deliver real business value. Stay at the forefront of AI/ML trends and emerging technologies, identifying opportunities to apply new techniques and tools. Support business development by contributing to proposals, pitching solutions, and identifying new areas for consultancy services. Requirements: MSc More ❯

Join a management consultancy that has been disrupting the industry for over a decade. They work across sectors including Defence, Retail, Government, and Healthcare, delivering bespoke Data Science and Machine Learning solutions. By combining strategy, innovation, and execution, they help organizations turn bold ideas into real-world impact Responsibilities: Own the end-to-end delivery of complex data … science and machine learning projects Define and drive data science strategies that align … with client goals and broader organizational objectives. Develop tailored models and algorithms to solve unique client problems to deliver real business value. Stay at the forefront of AI/ML trends and emerging technologies, identifying opportunities to apply new techniques and tools. Support business development by contributing to proposals, pitching solutions, and identifying new areas for consultancy services. Requirements: MSc More ❯

machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS, Azure) and tools like Dataiku and Databricks Experience with ML Ops, including deployment, monitoring, and More ❯

machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS, Azure) and tools like Dataiku and Databricks Experience with ML Ops, including deployment, monitoring, and More ❯

machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS, Azure) and tools like Dataiku and Databricks Experience with ML Ops, including deployment, monitoring, and More ❯

machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS, Azure) and tools like Dataiku and Databricks Experience with ML Ops, including deployment, monitoring, and More ❯

join a scaling startup in the Education sector Salary up to £70k , depending on experience Fully remote role (Europe-based) Tech stack: Python, LLMs, LangChain, AI Agents, SQL, GCP, ML If you wish to keep your CV/data private, feel free to WhatsApp your details/CV to me, Dan - WHO WE ARE: We're an EdTech startup developing … an AI-powered learning platform that helps university students prepare for exams and supports children in improving their reading and writing skills. As we continue to scale, we're expanding our AI capability - designing intelligent systems that personalise learning, generate insights, and drive student success. WHAT YOU WILL BE DOING: Design and develop AI-driven systems and tools … process (subject to required skills) your application to our client in conjunction with this vacancy only. KEY SKILLS: LLMs | LangChain | Agentic AI | AI Agents | Python | SQL | GCP | NLP | RAG | ML | AI Automation | Prompt Engineering More ❯

Qualifications • 6-10 years of experience in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Proven ability to assess or design More ❯