1 to 25 of 43 MLOps Jobs in the North West

validation and monitoring frameworks to ensure AI model performance, reliability and ongoing optimisation. You’ll establish and promote best practices for AI data pipelines, MLOps/AIOps, cloud infrastructure alignment and scalable architecture design. You’ll collaborate with Data Science, Data Engineering, Software Engineering and Enterprise Architecture teams to deliver ...

.Experience building and deploying Generative AI solutions, including prompt engineering, fine-tuning, and evaluation of large language models (LLMs) or other generative architectures.Understanding of MLOps principles, including automated model training, CI/CD for ML, model versioning, monitoring, and retraining.Experience deploying AI and GenAI solutions on cloud platforms (AWS, Azure ...

Computer Science, Machine Learning, or related field Nice to Have Published research in top ML venues (NeurIPS, ICML, ACL, CVPR). Experience with MLOps tools: MLflow, Weights & Biases, DVC. Familiarity with distributed training frameworks (DeepSpeed, Horovod). Experience with LLM fine-tuning and prompt engineering. Contributions to open-source ...

system design. Experience deploying and operating AI and machine learning services in production, including API-based architectures and cloud-hosted workloads. Practical experience with MLOps and AI lifecycle management, including data, model and environment versioning, automated deployment pipelines, monitoring and model retraining workflows. Experience leading complex technical projects from initial ...

Intelligence, Data Science, or a related technology discipline Minimum 2:1 degree classification (or equivalent) Desirable Azure OpenAI, AWS Bedrock and Google Gemini experience MLOps, Data Engineering or Platform Engineering experience Experience leading technical teams Knowledge of Agentic AI, AI Agents and emerging AI frameworks What's On Offer? Opportunity ...

workflow optimisation. Cloud and Deployment Knowledge - Familiarity with deploying AI models and AI-enabled services using cloud platforms such as AWS, Azure, or GCP, MLOps practices, cloud architecture, containerisation, model monitoring, and secure production deployment patterns. Problem-Solving and Communication skills - Ability to translate complex business and engineering challenges into ...

Hands-on experience in developing and deploying AI solutions in a professional setting.Experience building data pipelines and working with structured and unstructured data.Experience with MLOps tools and best practices for model deployment, monitoring, and governance.Experience working in Agile delivery environments.Strong analytical and problem-solving skills, with attention to detail.Programming: Strong ...

clients on AI platform capability and implementation strategy Tech environment: Python LLMs (prompt engineering, fine-tuning, RAG) LangChain/LangGraph Agent frameworks Vector databases MLOps/LLMOps AWS/Azure/GCP/Databricks Kubernetes & GPU infrastructure What you'll bring: - Experience designing enterprise AI or ML architectures - Strong grasp ...

engineering foundation with proficiency in Python, cloud platforms (AWS/Azure), APIs, and full-stack development to rapidly prototype and productionise AI applications.Experience with MLOps practices including model deployment, monitoring, evaluation, and CI/CD pipelines with delivering AI solutions from concept to production.Some other highly valued skills may include ...

data science solutions. Ensure sharing best practices and learnings with other squad members. Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance. Build standards and recommendations ...

equivalent platforms.Developing high-quality, maintainable code and working with software engineering practices such as version control, testing, code review and CI/CD.Working with MLOps or workflow tools such as MLflow, Kubeflow, Argo or equivalent frameworks.Scaling models or analytical services for enterprise or operational use.Applying statistical methods, model evaluation techniques ...

generative AI and the modern AI stack, including large language models, prompt engineering, retrieval-augmented generation (RAG), vector databases, evaluation/monitoring and MLOps principles, with the ability to shape investment cases and operating models at scale.Extensive experience providing executive oversight for production AI delivery (you steer architecture and engineering ...

habit of fixing the class of problem rather than the instance. AI and ML operations: Experience operating model serving, LLM inference or MLOps pipelines in production is a strong plus. Familiarity with model APIs, vector databases, MCP or orchestration frameworks helps. Networking and security: VPC design, service mesh and zero ...

controlStrong collaboration skills, working across engineering, security, data science and product teamsAnd it would be great if you had any of the following...Exposure to MLOps or SMLOps tooling and model lifecycle managementExperience supporting AI/ML pipelines, feature engineering or analytics platformsKnowledge of AI governance and secure adoption of generative ...

working with AWS-native data services and event-driven architecturesExperience building data products that support analytics, reporting, machine learning, or AI use casesKnowledge of MLOps, AI Engineering, Agentic AI, or Generative AI implementation patternsExperience leading distributed engineering teamsExperience establishing engineering standards, reusable frameworks, and community-of-practice initiativesKnowledge of data ...

agreed requirements, delivery plans and quality standards.Support the deployment and operationalisation of AI systems, including model monitoring, performance optimisation, CI/CD and MLOps practices.Collaborate with solution architects, data scientists, business analysts and engineers to ensure AI solutions are integrated effectively into wider technology and business environments.Apply responsible AI, security … equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible AI considerations. Understanding of MLOps and production AI practices, including CI/CD, model versioning, monitoring, automated testing, retraining and performance optimisation. Experience using cloud platforms and cloud-native ...

environments. You will play a key role in designing, building, and maintaining scalable, secure, and high-performing infrastructure, while working closely with Data Engineers, MLOps Engineers, and Solution Architects. Key Responsibilities Design, build, and maintain CI/CD pipelines using GitLab CI for reliable, automated deployments to Azure Kubernetes Service ...

including machine learning models, data pipelines and application components that are secure, reliable and performant.Drive the operationalisation of AI solutions using modern engineering and MLOps practices, including CI/CD, model monitoring, testing and lifecycle management.Ensure solutions are developed in line with security, privacy, governance and responsible AI requirements, particularly … practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation approaches.Experience with MLOps and modern engineering practices, including CI/CD pipelines, model versioning, monitoring and automated testing.Experience deploying AI solutions on cloud platforms such as Azure ...

growth over the last few years and we’re looking to continue with this momentum as we build on our reputation as Open Source MLOps and applied AI experts, expand our role within the community, and continue to deliver high-quality solutions to our clients. What we’re looking … also enjoy being part of a culture that values: Loving what we do: a real passion for open source, applied AI, MLOps, and taking pride in our work. Just trying it: AI is moving quickly. We love to develop new skills, solve new problems and thrive on a challenge. Being ...

into complex enterprise workflows.Bridge Design & Implementation: Oversee the full technical lifecycle, from selecting the right model architectures to ensuring robust CI/CD and MLOps pipelines.Inference & Infrastructure: Deploy and optimise models using cloud services like AWS Bedrock and Azure AI Foundry, or self-host them on GPU/CPU hardware … Evaluation: Implement frameworks and approaches to evaluate model performance against business objectives, both pre-deployment and on an ongoing basis as part of the MLOps lifecycle.Drive System Performance: Assess and optimise for performance, cost-efficiency, and reliability, ensuring AI outputs meet the rigorous standards required for our Security & Justice clients.System ...

Fuzzy Labs, a Manchester-based tech consultancy, seeks a Lead Applied AI Engineer to guide squads, own client projects from discovery to production, and shape technical direction. You'll mentor engineers, collaborate with customers, and ...

maintain end-to-end AI/ML pipelines in Microsoft Fabric Design, train, deploy, and monitor machine learning and deep learning models Implement MLOps best practices: versioned data & features, CI/CD pipelines, model promotion, and rollback Collaborate with data scientists, analytics engineers, product managers, and developers to turn business … augmented generation Knowledge of AutoML, hyperparameter tuning and advanced MLflow features Experience with streaming and real-time data platforms Familiarity with CI/CD, MLOps and deployment pipelines (Azure DevOps, GitHub Actions, Docker) Commercial awareness in e-commerce, travel or holiday-lettings sectors Experience mentoring others or leading technical workstreams ...

qualification in relevant field (eg Computer Science, Data Science, Operational Research) Experience with modern data platforms (eg Databricks, Snowflake, MS Fabric). Familiarity with MLOps practices and version control tools (e.g. Git). Experience with deployment and maintenance of ML models in production environments. SQL MS Excel Power BI Python ...

solutions are based on sophisticated analytical thought and research. Qualifications & Skills AI/ML Architecture: AI/ML frameworks, multi‐cloud platforms, data architectures, MLOps, and secure, scalable enterprise AI solution design. Enterprise Architecture & Governance: EA frameworks, AI governance, ethical AI, compliance, and alignment to business and IT strategy. Stakeholder ...

workloads on AWS (or multi‐cloud with strong AWS depth).Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components).Proven ability to take research and prototype ...