16 of 16 Contract MLOps Jobs in the UK excluding London

methods? Any experience of popular known deployment methods on k8s cluster? Gitops/Git/Jenkins Any experience using gitops pipeline? Nice to have Understanding of LLM Evaluation Frameworks MLOps platforms or LLMOps background Understanding of AI Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates More ❯

must be current) Strong experience in AI/ML engineering (Python, TensorFlow, PyTorch, etc.) Experience with cloud platforms (AWS, Azure, or GCP) Solid understanding of data pipelines, APIs, and MLOps Excellent problem-solving and communication skills More ❯

we’re looking for: Proven experience in AI/ML model development and deployment Strong skills with Python, TensorFlow/PyTorch, and cloud platforms (AWS/Azure/GCP) MLOps assurance and risk experinece Knowledge of data pipelines, model optimisation, and real-world deployments Details: Contract: 6 months (with view to extend) Location: London (Hybrid) Start: ASAP If you’re More ❯

on experience as a DevOps engineer with Google Cloud Platform. Proven expertise with AI/ML services on GCP, particularly Vertex AI, BigQuery ML, and TensorFlow. Solid understanding of MLOps principles, including building CI/CD pipelines for machine learning. Proficiency in Infrastructure as Code (IaC) using Terraform. Experience deploying and managing AI/ML workloads with Kubernetes/GKE. More ❯

on experience as a DevOps engineer with Google Cloud Platform. Proven expertise with AI/ML services on GCP, particularly Vertex AI, BigQuery ML, and TensorFlow. Solid understanding of MLOps principles, including building CI/CD pipelines for machine learning. Proficiency in Infrastructure as Code (IaC) using Terraform. Experience deploying and managing AI/ML workloads with Kubernetes/GKE. More ❯

initiatives. Experience required: AWS Data/ML Engineering & ML Ops (ECS, Sagemaker) CI/CD pipelines (GitLab, Jenkins) Python, PySpark & Big Data ecosystems AI/ML lifecycle, deployment & monitoring MLOps tooling (MLflow, Airflow, Docker, Kubernetes) Front-end exposure (HTML, Flask, Streamlit) RESTful APIs & backend integration If this ML Engineer role is of interest, please apply now for immediate consideration. More ❯

ML architecture and system design (minimum 2 years) with proven expertise in hands-on coding AI solutions. Deep knowledge of machine learning frameworks, cloud platforms (AWS, Azure, GCP), and MLOps(machine learning operations) practices. Deep knowledge about design and implementation of secure integrations between AI solutions and legacy enterprise software, whilst ensuring compliance with government-level security requirements, implementing single More ❯

Senior Data Engineer (AI & MLOps) - Software - Newcastle/Hybrid or Remote Day rate: £300 - £500 (Inside IR35) Duration: 6 months Start: ASAP My new client is looking for a Senior Data Engineer with expertise in AI, MLOps, and AWS architecture to design and deliver production-grade machine learning pipelines. The ideal candidate will be passionate about bridging the gap between … compliance of data pipelines and deployed ML solutions. Mentor junior engineers and contribute to setting technical standards for the team. Required Qualifications Proven experience as a Senior Data Engineer, MLOps Engineer, or similar role. Strong background in data structures, algorithms, and software engineering principles. Advanced proficiency in Python for data wrangling, pipeline automation, and ML workflows. Expertise in AWS services More ❯

maintain secure AWS cloud infrastructure Implement and manage CI/CD and DevOps pipelines Champion data quality, security, and best practices Collaborate with cross-functional teams Implement and manage MLOps capabilities Essential Skills: Advanced Python programming skills Expertise in data engineering tools and frameworks (Apache Flink) Hands-on AWS experience (Serverless, CloudFormation, CDK) Strong understanding of containerization, CI/CD More ❯

reinforcement learning Model selection, training, validation, and evaluation Deep learning architectures (CNNs, RNNs, Transformers) Data Science Statistical analysis, feature engineering, A/B testing Experiment design and hypothesis testing MLOps & Engineering Scalable ML systems (batch and real-time) ML pipelines, CI/CD, monitoring, deployment Familiarity with tools like MLflow, Kubeflow, Airflow, Docker, Kubernetes Strategic skills Align ML initiatives with More ❯

ML architecture and system design (minimum 2 years) with proven expertise in hands-on coding AI solutions Deep knowledge of machine learning frameworks, cloud platforms (AWS, Azure, GCP), and MLOps(machine learning operations) practices. Deep knowledge about costing of AI models to produce reasonable ROI and modular reusable services with moderate level of maintenance Understanding of data architecture, API design More ❯

development, ideally in regulated industries. Sector Knowledge: Financial services, consulting, or technology background with a focus on transformation. Technical Understanding: Familiarity with AI/ML technologies (generative AI, NLP, MLOps, data governance). Business Acumen: Ability to identify high-impact AI use cases aligned to business strategy. Governance Awareness: Strong understanding of risk, compliance, and model governance in a complex More ❯

as a C# Developer with proficiency in Python, .NET framework and C# as well as experience with ML.NET, ASP.NET, MVC, Web API Containers (Docker/Kubernetes), Machine Learning Operations (MLOps) and CI/CD Good knowledge of IT industry trends (especially GenAI and AgenticAI), suppliers, platforms and products Post productions MLOps, Model retaining and Drift monitoring in Azure with knowledge More ❯

Job Title: ML Ops/LLM Ops Engineer Location: Hybrid (potentially 1 day per week in east London) Contract: 6 month Contract Day Rate: £400 per day (Outside IR35) About the Role We are seeking an experienced ML Ops/ More ❯

Role? Shape and deliver the security architecture strategy for enterprise cloud and AI/ML programmes. Work on cutting-edge initiatives in the financial services domain, integrating AI and MLOps with security guardrails. Act as a trusted advisor to senior leadership , influencing both business and technology direction. Key Responsibilities Define and evolve security architecture strategies for cloud, AI/ML … and MLOps environments . Act as a senior security advisor to leadership, engineering, and business stakeholders. Develop security architecture standards, patterns, and guidelines for enterprise solutions, with specific coverage for AI/ML workloads. Conduct security architecture reviews, threat modelling, and risk assessments for AI/ML systems and pipelines . Ensure solutions comply with European financial services regulations (GDPR … PSD2, DORA, NIS2) as well as emerging AI governance frameworks (e.g., EU AI Act, NIST AI RMF). Integrate security into DevSecOps and MLOps pipelines , including CI/CD and infrastructure-as-code environments. Drive adoption of Zero Trust principles, encryption standards, IAM policies, and network/data/application security controls. Collaborate with data scientists, ML engineers, and IT More ❯

to join our team in Radbroke. This hybrid role offers the opportunity to work on cutting-edge machine learning and data engineering projects, leveraging the latest cloud technologies and MLOps practices. Required/Primary Skills: AWS Data Engineering ML Engineering ML-Ops ECS, Sagemaker Gitlab Jenkins CI/CD AI Lifecycle Experience in front-end development (HTML, Stream-lit, Flask … with model deployment and monitoring in cloud environments (AWS). Understanding of machine learning lifecycle and data pipelines. Proficiency with Python, Pyspark, Big-data ecosystems Hands-on experience with MLOps tools (e.g., MLflow, Airflow, Docker, Kubernetes) Secondary Skills Experience with RESTful APIs and integrating backend services All profiles will be reviewed against the required skills and experience. Due to the More ❯