26 to 42 of 42 MLOps Jobs in the North West

deploy scalable solutions that drive real business value. You will master Python, SQL and cloud platforms, work on generative AI, AI governance and MLOps, gaining hands-on experience across fraud detection, credit risk and customer analytics in a supportive, ethics-first environment. #J-18808-Ljbffr ...

agentic technologies, end‐to‐end. Skills and Experience Proven leadership experience in Gen AI delivery Hands‐on technical understanding of modern AI tooling, MLOps, and model deployment and generative/agentic AI frameworks Commercial mindset, experience bringing AI, including generative, use cases into production Strong communication skills and the ability ...

architectural expertise across AWS and Azure, alongside experience with modern data platforms such as Snowflake and Databricks. Experience with AI/ML, MLOps and responsible AI is important, as is the ability to operate confidently with both technical teams and senior business stakeholders. We're looking for someone ...

Lambda, IAM, VPC, KMS, or Bedrock. Experience developing or contributing to scalable architectures for data-driven products or services. Experience working with MLOps practices or machine learning workflows. Experience with containerisation and orchestration technologies. Familiarity with machine learning concepts, statistical techniques, or machine learning frameworks, and experience collaborating with data ...

code, CI/CD pipelines, containerisation and cloud governance to ensure platforms are secure, scalable and auditable, with close collaboration to data engineers, MLOps engineers and solution architects. #J-18808-Ljbffr ...

implementation leadership for major features and platform initiatives, including writing and reviewing critical-path code where the work demands it. Define and oversee the MLOps strategy spanning model training, deployment, monitoring, and lifecycle management on Kubernetes across AWS, GCP, and Azure. Establish and evangelize engineering best practices across services, including … experience with Kubernetes and at least one major cloud provider (AWS, GCP, or Azure), with working familiarity across multi-cloud environments. Demonstrated experience with MLOps tooling and patterns, including model registries, experiment tracking, and CI/CD for. Proven ability to lead architectural strategy across multiple teams and services, balancing ...

seeking an AI Platform & Site Reliability Engineering Managing Consultant to design, build and scale secure AI platforms. You will integrate SRE, observability and MLOps, guiding senior clients from strategy to delivery. This role offers flexible hybrid working across Manchester, Glasgow or London, with leadership of multidisciplinary teams and governance shaping ...

strengthen platforms that support data, AI, and automation across the organisation. You will guide standards, coach colleagues, and help drive DataOps, AIOps and MLOps improvements while working in a hybrid setup with 50% home/office. #J-18808-Ljbffr ...

customers. They will be subject matter experts in the areas of Predicative AI, Machine Learning, Generative AI along with associated capabilities in areas like MLops, Data Pipelines, and DevOps. The role will interface directly with the customers' business, data science and IT Operations teams to establish CDW credibility and position … learning, lab time and formal training. What you will do Position CDW Custom AI capabilities - Engage with all Customer AI personas: technical personas (CDO, MLOps, AI/ML Engineer, Data Scientist), outcome-driven personas (CEO, CTO, LOB) and ITDMs (CIO, VP Infrastructure). Technical SME on CDW Custom AI – Maintain ...

This job is with Capgemini, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. CAPGEMINI INVENT At Capgemini Invent, we ...

promote best practice across Data & AI Operations. Lead continuous improvement, including optimising long-running data pipelines and operational processes. Support DataOps, AIOps and MLOps activities across the team. Oversee the operational monitoring and governance of AI solutions, including emerging agentic AI capabilities. Support the implementation and ongoing optimisation of Databricks … enthusiasm for emerging AI technologies. It would be great if you also had Experience with Databricks. Experience with Azure or AWS. Exposure to MLOps or AI Operations. Experience with Power Apps or the wider Power Platform. Experience in financial services. At Royal London, you’ll be part of a mutual ...

Engine behind the Syrup platform and Anaplan’s forecasting solutions. The team is responsible for the production execution of forecasting and predictive models, the MLOps infrastructure supporting our data scientists, and the data processing services that deliver insights to enterprise customers. This role reports to the Director of Engineering … implement scalable, fault-tolerant predictive intelligence services and features as a core contributor to the ML Engine backend. Lead the technical implementation of MLOps capabilities, including model training pipelines, deployment workflows, and runtime infrastructure for production ML. Partner with data scientists to productionize models and graduate experimental work into stable ...

Platform Strategy & Architecture: Assess, define and evolve enterprise AI platform architectures, covering LLM and agentic frameworks, AI gateways, model lifecycle management, data platforms, MLOps/LLMOps foundations and integration patterns. Support clients in evaluating build, buy and hybrid approaches aligned to business needs, risk appetite and operational requirements.• AI Platform … operating cloud-native, platform engineering, AI platform or reliability engineering solutions within complex enterprise environments. • Strong understanding of AI platform architectures including LLMOps, MLOps, agentic AI frameworks, model lifecycle management and AI operational controls. • Experience establishing and scaling SRE practices including observability, SLIs, SLOs, error budgets, incident management and reliability ...

deliver solutions to complex problems. Develop and expand Data Science capabilities and support capability building within the organisation. Manage machine learning deployment pipelines (MLOps) and resolve potential bottlenecks. Mentor and coach other engineers to support their professional development. About the Candidate Essential Experience Extensive experience in Python and proficiency … other languages (e.g., SQL, R, Java). Strong experience deploying and monitoring machine learning (MLOps) using tools such as MLflow, AWS Sagemaker, and Azure Machine Learning. Proven track record of delivering high-quality, scalable data science solutions. Expertise in Data Manipulation, ML, and Statistical Analysis coding packages. Strong experience ...

supporting AI/ML workloads. You'll apply deep technical expertise across infrastructure automation, environment provisioning and deployment pipelines , working closely with Data Engineers, MLOps Engineers and Solution Architects to ensure the platform meets performance, scalability, cost and compliance requirements. There is flexibility on base location across … Vault and Azure AD Supporting connectivity between on-prem services and Azure cloud infrastructure (hybrid networking/private connectivity, including GreenLink) Working with MLOps and Data Engineers to ensure environments are reproducible, reliable and auditable across multiple environments Supporting observability and platform health: logging and metrics monitoring using tooling such ...

operate AI infrastructure for enterprise AI workloads. You’ll work across hybrid and multi-cloud environments, delivering GPU-accelerated compute, model serving, and MLOps tooling while guiding clients through transformations. You will lead architecture reviews, workshops, and implementation of observability, security, and governance frameworks for AI systems. #J-18808-Ljbffr ...

powering forecasting solutions, working with data scientists and platform partners to productionize models and maintain high-availability production systems. You will design and operate MLOps pipelines, deployment workflows, and runtime infrastructure across cloud environments, aiming for performance, scalability, and cost efficiency. #J-18808-Ljbffr ...