15 of 15 Contract MLOps Jobs in London

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 ❯

mining, or similar). Proven track record of building or deploying GenAI/LLM systems into production. Strong Python skills, with experience in PyTorch or TensorFlow . Understanding of MLOps practices (evaluation, monitoring, scaling). Master's (or equivalent experience) in Computer Science, AI, ML, or related field. Bonus points for: experience designing annotation schemas, Kaggle Master credentials, or published 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

ML solutions to ensure safety, reliability, and compliance. Advise teams on ethical, regulatory, and operational compliance , integrating AI governance into project delivery. Support safe deployment of AI systems, guiding MLOps best practices and risk mitigation strategies. Candidate Requirements: Active SC clearance (DV desirable). Deep technical expertise in AI/ML , including hands-on experience with model development, deployment, and More ❯

MLOps Engineer Our trusted partner, which operates within the Ed-Tech domain, employs over 10,000 individuals across 100 countries and has a reach of 600 million users, is recruiting an MLOps Engineer who has Chatbot (Voice) integration project experience using Python, Pytorch, Pyspark and AWS LLM/Generative AI. Our client is paying £400 PD Outside IR 35 to More ❯

Senior Machine Learning Operations Engineer London (2x a week onsite) - £500 p/d (Outside IR35) 6-months Contract We are seeking an experienced MLOps Engineer to join a globally known consumer tech company focused on building innovative, large-scale platforms. In this role, you will evolve and scale the machine learning platform, ensuring it supports high-throughput model inference … and fast iteration cycles. This position is perfect for someone who thrives at the intersection of MLOps, Kubernetes, and cloud infrastructure, with a hands-on approach to solving complex challenges. You will work closely with ML engineers and product teams to align infrastructure with evolving project needs, research and implement cutting-edge MLOps practices, and mentor colleagues by sharing expertise … clusters from scratch, configuring them manually using tools like kubeadm, and deploying applications with Helmdemonstrating true infrastructure-level expertise rather than just deploying services on managed platforms. Key Skills MLOps & Kubernetes: GPU-enabled cluster management, built from scratch using kubeadm and Helm. Programming : Python or Go for ML automation workflows. Containerization : Docker and containerized application deployment. Cloud : AWS experience supporting More ❯