101 to 125 of 476 MLOps Jobs in the UK excluding London

products, including customer personalization tools, demand forecasting systems and dynamic pricing solutions Lead the development, deployment and monitoring of Gen AI/ML models with a strong focus on MLOps and operational scalability Establish and oversee AI governance frameworks to ensure compliance with regulatory standards, ethical practices and measurable business value Leverage Gen AI technologies, including LLMs and Retrieval-Augmented More ❯

PREFERRED QUALIFICATIONS: Meteorological understanding/experience with weather modelling Prior knowledge or experience in the power markets or energy sector. Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps practices. Familiarity with data visualization tools (e.g., Tableau, Power BI). COMPENSATION & BENEFITS: Competitive salary + bonus. Hybrid working arrangement (minimum 3 days in the London office) #J-18808-Ljbffr More ❯

services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments Monitor and manage model performance, including addressing issues related to explainability, data drift and model drift in financial models Collaborate with risk, compliance and More ❯

services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments Monitor and manage model performance, including addressing issues related to explainability, data drift and model drift in financial models Collaborate with risk, compliance and More ❯

services use cases, such as credit scoring, fraud detection, customer segmentation and predictive modeling Lead the process of taking AI/ML models from development to production, ensuring robust MLOps practices tailored to financial data environments Monitor and manage model performance, including addressing issues related to explainability, data drift and model drift in financial models Collaborate with risk, compliance and More ❯

domains Expertise in model validation, explainability, governance and ethical AI principles Advanced proficiency in Python (e.g. Scikit-learn, TensorFlow/PyTorch) and SQL, plus familiarity with ML engineering and MLOps practices Nice to have: Experience in setting or influencing data science strategy in a growing organisation Familiarity with AWS SageMaker and modern cloud-based ML workflows History of publications, open More ❯

of the development lifecycle from idea generation to testing, implementation and ensuring business value across different business areas and markets. With the support of more senior data scientists and MLOps engineers, you will ensure that solutions are rigorously tested, deliver business value and are then optimised over their lifecycle. We expect solutions to make use of efficient algorithms whilst enabling More ❯

and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow More ❯

and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow More ❯

e.g., Kafka, Spark Streaming). Proficiency in CI/CD pipelines for data deployment using Azure DevOps, GitHub Actions, or Terraform for Infrastructure as Code (IaC). Understanding of MLOps principles, including continuous integration (CI), continuous delivery (CD), and continuous training (CT) for machine learning models. Experience with performance tuning and query optimisation for efficient data workflows. Strong understanding of More ❯

with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯

with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯

will also oversee traditional deep learning model development from design, training, evaluating to deployment, with a focusing on fine turn LLMs. The role will interact with product, design, engineering, MLops, and domain experts and partners. When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives More ❯

Senior MLOps Engineer - Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability …/CD pipelines, monitoring systems, and infrastructure automation. Upholding best practices in security, cost management, and infrastructure design for cloud environments. The Ideal Candidate: 4+ years of experience in MLOps, DevOps, or software engineering roles. Strong programming skills in Python and familiarity with ML frameworks. Extensive experience with AWS services (e.g., SageMaker, ECS, Lambda) and cloud environments. Proficiency with containerization More ❯

Senior MLOps Engineer Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability More ❯

Senior MLOps Engineer Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability More ❯

Senior MLOps Engineer Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability More ❯

Senior MLOps Engineer Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability More ❯

Senior MLOps Engineer Hybrid/Dundee Salary up to £70,000 We are looking for a Senior MLOps Engineer to join a Scottish company working on cutting edge AI solutions. You will play a pivotal role in ensuring that ML initiatives drive value effectively while maintaining operational excellence. The Role: Managing and optimising existing ML model deployments to ensure reliability More ❯

an inclusive employer and a member of myGwork – the largest global platform for the + business community. Please do not contact the recruiter directly. Job Details Job Title: Principal MLOps/GenAI Infrastructure Engineer Salary: £76,700 - 87,600 (The expected salary range for this role reflects internal benchmarking and external market insights.) Band: D Location: London/Salford/… and do the best work of their careers. Your Key Responsibilities And Impact Lead the design, development, and evolution of robust tooling and platforms to support scalable Data Science, MLOps, and LLMOps workflows across the organisation. Drive strategy and execution for deploying, serving, and monitoring large models (LLMs) in real-time and batch environments using Amazon SageMaker, Bedrock, and related … culture through mentorship, knowledge sharing, and thought leadership via deep dives, brown bags, internal tech talks, and cross-team collaboration. Your Skills And Experience Extensive experience in DevOps/MLOps roles with demonstrated impact in building, scaling, and securing ML/AI infrastructure in cloud- environments. Strong experience with AWS services such as SageMaker, Bedrock, S3, EC2, Lambda, IAM, VPC More ❯

team will design and deploy advanced models that improve supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation. You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery . This is a hybrid role , with flexibility to work from … mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems. Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions. Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines. Champion the integration of model outputs into wider data and reporting platforms. Clearly communicate technical insights and model outcomes … functional squads. What You’ll Get in Return A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance. Dedicated support from MLOps and Engineering teams to accelerate delivery. Access to career development support including coaching, mentoring, and leadership training . A competitive salary package including car allowance , bonus , and comprehensive benefits such More ❯

Experience developing AI/ML solutions using Python? * Knowledge of frameworks such as PyTorch (preferred), TensorFlow, or Scikit-learn? * Experience with NLP, deep learning, or computer vision? * Familiarity with MLOps tools (Azure ML Pipelines, MLflow, Docker, Kubernetes)? * Experience working with cloud platforms such as Azure, GCP, or AWS? * The abbility to engage with technical and non-technical teams? Would you … prospects and a strong benefits package, including hybrid working, bonus schemes, private healthcare and more? If so, please apply! Python | AI | Machine Learning | NLP | Deep Learning | Azure | PyTorch | TensorFlow | MLOps | Kubernetes | OpenAI | CI/CD | Software Engineering | LegalTech All of our opportunities require that applicants are eligible to work in the specified country/location, unless otherwise stated in the More ❯

client requirements into scalable, cloud-based AI architectures that address both technical feasibility and business impact. Propose end-to-end AI/ML solutions—including model design, data pipelines, MLOps, and platform integration—tailored to each opportunity. 3. Support Sales and Bid Activity Lead the technical response for AI-related RFPs, RFIs, and proposals, including solution overviews, technical narratives, architecture … them with AI/ML solutions in cloud environments (Azure, AWS, or GCP). Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), estimate effort More ❯

client requirements into scalable, cloud-based AI architectures that address both technical feasibility and business impact. Propose end-to-end AI/ML solutions-including model design, data pipelines, MLOps, and platform integration-tailored to each opportunity. 3. Support Sales and Bid Activity Lead the technical response for AI-related RFPs, RFIs, and proposals, including solution overviews, technical narratives, architecture … them with AI/ML solutions in cloud environments (Azure, AWS, or GCP). Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), estimate effort More ❯

client requirements into scalable, cloud-based AI architectures that address both technical feasibility and business impact. Propose end-to-end AI/ML solutions—including model design, data pipelines, MLOps, and platform integration—tailored to each opportunity. Support Sales and Bid Activity Lead the technical response for AI-related RFPs, RFIs, and proposals, including solution overviews, technical narratives, architecture diagrams … them with AI/ML solutions in cloud environments (Azure, AWS, or GCP). Deep technical understanding of AI/ML concepts: supervised and unsupervised learning, GenAI, LLMs, embeddings, MLOps, vector search. Experience designing solutions using tools such as Azure ML, AWS SageMaker, Google Vertex AI, Databricks, LangChain, and Hugging Face. Ability to develop architecture artefacts (e.g., HLDs), estimate effort More ❯