15 of 15 Remote/Hybrid MLOps Jobs in Central London

testing, and statistical evaluation. Proven track record transitioning models from experimentation to production with governance and quality controls. Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC). Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures. Familiarity with LLMOps tooling (LangSmith, LangChain, LangGraph). ...

proposals, and PoC preparations, collaborating with Data/AI Engineers on full lifecycle deployments Build & deploy scalable solutions: create data pipelines (ETL/Airflow), MLOps (Docker/AWS/Azure/GCP), and interactive dashboards (Tableau/Power BI) Drive client impact – from EDA and model validation to ethics-compliant ...

applied AI Desirable Experience Hands-on experience with AWS services such as Lambda, ECS, S3, SageMaker or Bedrock Knowledge of ML engineering and MLOps practices (e.g. Docker, MLflow) Experience working in government, defence or other highly regulated environments Proven application of large language models (LLMs) to real-world problems Security ...

security clearance; sponsorship cannot be provided. Desirable: Knowledge of AWS services (e.g., Lambda, ECS, Bedrock, S3, SageMaker). Experience with ML engineering and MLOps (e.g., Docker, MLflow). Experience in regulated industries or government-related projects. Applying LLMs or advanced AI methods to real-world problems. Benefits: Competitive salary ...

Services, and Azure Machine Learning. Familiarity with Azure Databricks is a plus. Understanding of CI/CD pipelines, containerization (Docker, Kubernetes), and experience implementing MLOps practices using Azure DevOps. Qualifications such as the following would be advantageous, however not necessary: Microsoft Azure AI Engineer Fundamentals/Associate Microsoft Azure Data ...

Databricks, LangChain , vector databases , or LLM orchestration tools . Knowledge of RAG pipelines , transformers , and modern AI architectures . Understanding of deployment or MLOps best practices (Azure experience a plus). Recent, hands-on experience with applied LLM projects . Strong communication and stakeholder engagement skills. A Master’s degree ...

growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ...

deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker, ECS, Lambda, S3, Bedrock) MLOps/ML engineering experience (Docker, MLflow) Experience in government or regulated environments Practical experience applying LLMs Security Clearance UKIC DV eligible required ...

junior team members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision, or time-series analysis Ability to design experiments and apply statistical validation Understanding of Responsible ...

work from home. The AI Engineer will support delivery of AI use cases, workflows, analytics and solutions - responsible for tasks such as pattern recognition, MLOps, software development, neural networks, and natural language processing on a day-to-day basis. Qualifications Pattern Recognition and Neural Networks skills Computer Science and Software ...

experimental models into production-ready solutions, collaborating with engineers on deployment, monitoring, and optimisation. Build and maintain ML pipelines using AWS services and modern MLOps/LLMOps tooling. Implement robust versioning, experiment tracking, and reproducibility practices. Mentor junior engineers and contribute to team-wide AI knowledge sharing. Communicate complex technical … level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record transitioning models from experimentation to production with governance and quality controls. Experience developing ...

create real commercial leverage Skills and Experience Proven leadership in defining and delivering enterprise AI strategy, including GenAI Strong understanding of AI platforms, MLOps, and modern AI tooling (without needing to be hands-on) Experience translating AI opportunities into commercially impactful use cases at scale Exceptional communication, influence, and stakeholder ...

Collaborate with product and engineering to integrate ML systems into user-facing features Develop and deploy production-quality machine learning frameworks, while maintaining robust MLOps pipelines Stay up-to-date with the latest advancements in AI, conduct research, and explore innovative techniques Influence key decisions on architecture and implementation … including latency, token cost control, context window constraints, monitoring and prompt versioning Strong Python skills and experience with PyTorch, TensorFlow or Keras Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI Bachelor's degree in a technical field such as computer science or years ...

patterns, oversee solution design, guide engineering teams, and ensure alignment with security, compliance, and responsible AI standards. The role spans GenAI , ML , data platforms , MLOps , prompt engineering , and application integration . Key Responsibilities Architecture & Design Define end-to-end AI reference architectures across data, model lifecycle, APIs, and app integrations … Select and benchmark models (OpenAI, Azure AI Foundry, OSS LLMs) for task fit, cost, latency, and accuracy; design RAG and fine‐tuning strategies. Establish MLOps/LLMOps pipelines (CI/CD, feature stores, monitoring, drift detection, human-in-the-loop). Delivery Leadership Translate business objectives into solution roadmaps, epics ...

MLOps Engineer Location: London, UK (Hybrid – 2 days per week in office) Day Rate: Market rate (Inside IR35 Duration: 6 months Role Overview As an MLOps Engineer, you will support machine learning products from inception, working across the full data ecosystem. This includes developing application-specific data pipelines, building ...