13 of 13 Contract MLOps Jobs in London

LangChain, LlamaIndex, and RAG architectures. Build APIs and microservices for scalable AI deployment. Use AI-powered dev tools like GitHub Copilot, Cursor, and Codeium to speed up iteration. Apply MLOps/LLMOps practices with MLflow, Weights & Biases, and Kubeflow. ?? Youll Bring Strong Python skills and experience with LangChain, Transformers, Hugging Face. Solid grasp of LLM behavior, prompt optimization, and data More ❯

algorithms based on project requirements. Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert proof-of-concept models into production-grade pipelines in collaboration with MLOps and engineering teams. Required: Translate model outcomes into actionable insights through clear storytelling and visualizations. Build dashboards and reports using Power BI, Tableau, or Python-based visualization tools. Communicate findings More ❯

CI/CD pipelines, and GitHub Actions. Knowledge of containerization (tools ie Docker) and orchestration (ie Kubernetes on Azure). Good awareness of Data & AI - understanding of ML lifecycle, MLOps, and Responsible AI. Strong problem-solving and analytical skills. Excellent communication and stakeholder management skills. Nice to have: Familiarity with LLM fine-tuning. Strong academic background in IT/Computer More ❯

and analyse large, complex datasets. Strong understanding of data ethics, governance, and responsible AI principles. Must have SC Clearance and 5 years' continuous UK residency . Desirable: Experience with MLOps or deploying ML models into production. Familiarity with data engineering workflows and pipelines. Knowledge of working in a secure or public sector environment. If you believe your experience is in More ❯

and analyse large, complex datasets. Strong understanding of data ethics, governance, and responsible AI principles. Must have SC Clearance and 5 years' continuous UK residency . Desirable: Experience with MLOps or deploying ML models into production. Familiarity with data engineering workflows and pipelines. Knowledge of working in a secure or public sector environment. If you believe your experience is in More ❯

Qualifications: • 6+ years of experience in applied data science, machine learning, or analytics leadership. • Strong understanding of model lifecycle management, experimentation frameworks, and data science governance. • Familiarity with MLOps concepts and tooling (e.g., MLflow, Kubeflow, Vertex AI, SageMaker, Azure ML). • Hands-on experience with data science tools and languages such as Python, R, SQL, and relevant frameworks (e.g., scikit More ❯

agile delivery approach, consistently documenting designs and results for leadership. Experience and Expertise Required We are looking for hands-on experience in the following core areas: Model Lifecycle Management (MLOps): Proven experience in implementing robust AI/ML pipelines for model training, validation, and deployment (e.g., using MLflow, Vertex AI, or Azure ML). Expertise in managing model evaluation, drift More ❯

agile delivery approach, consistently documenting designs and results for leadership. Experience and Expertise Required We are looking for hands-on experience in the following core areas: Model Lifecycle Management (MLOps): Proven experience in implementing robust AI/ML pipelines for model training, validation, and deployment (e.g., using MLflow, Vertex AI, or Azure ML). Expertise in managing model evaluation, drift More ❯

MLOps Engineer Outside IR35 - 500-600 Per Day Ideally, 1 day per week/fortnight in the office, flexibility for remote work for the right candidate. A market-leading global e-commerce client is urgently seeking a Senior MLOps Lead to establish and drive operational excellence within their largest, most established data function (60+ engineers). This is a mission … critical role focused on scaling their core on-site advertising platform from daily batch processing to real-time capability. This role suits a hands-on MLOps expert who is capable of implementing new standards, automating deployment lifecycles, and mentoring a large engineering team on best practices. What you'll be doing: MLOps Strategy & Implementation: Design and deploy end-to-end … MLOps processes, focusing heavily on governance, reproducibility, and automation. Real-Time Pipeline Build: Architect and implement solutions to transition high-volume model serving (10M+ customers, 1.2M+ product variants) to real-time performance. MLflow & Databricks Mastery: Lead the optimal integration and use of MLflow for model registry, experiment tracking, and deployment within the Databricks platform. DevOps for ML: Build and automate More ❯

Communicate complex concepts to all stakeholders. At least 3 years of experience in AI solution engineering. Large Language Models experience including prompt engineering and RAG implementations. Expert data analytics, MLOps practices and API development. Desirable knowledge in Docker and Kubernetes More ❯

with internal policies and external regulations. Provide technical input on risk mitigation strategies and onboarding documentation. Security & DevSecOps Integration: Integrate AI security controls into CI/CD pipelines and MLOps workflows. Use tools such as Azure Key Vault, Microsoft Entra ID, and GitHub Actions for secure deployment and access management. Monitor AI systems using Azure Monitor, Log Analytics, and Application More ❯

integrating with live data feeds and cloud infrastructure. Research and prototype cutting-edge AI techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data … analytics TO BE CONSIDERED Please apply directly by emailing with your CV and availability. KEYWORDS: AI Engineer, Machine Learning Engineer, Sports Analytics, Computer Vision, Deep Learning, Python, TensorFlow, PyTorch, MLOps, Data Science, Predictive Modelling, Sports Tech, AI in Sports More ❯

. Develop pipeline programming using Python, Spark, and SQL; integrate APIs for seamless workflows. Support Machine Learning and AI initiatives, including NLP, Computer Vision, Time Series, and LLMs. Implement MLOps, CI/CD pipelines, data testing, and quality frameworks. Act as an AI super-user, applying prompt engineering and creating AI artifacts. Work independently while providing clear justification for technical … Proficient with cloud platforms (Snowflake, AWS fundamentals). Solid understanding of data architecture, warehousing, and modeling. Programming expertise: Python, Spark, SQL, API integration. Knowledge of ML/AI frameworks, MLOps, and advanced analytics concepts. Experience with CI/CD, data testing frameworks, and versioning strategies. Ability to work effectively in multi-team, vendor-integrated environments. Why This Role Join a More ❯