1 to 25 of 40 Permanent MLOps Jobs in the City of London

Snowflake, and cloud platforms Implement batch and real-time data processing with structured and unstructured data Deploy solutions on cloud with CI/CD, MLOps tools, and ensure production reliability Collaborate with business teams, ensure compliance, and mentor teams on best practices Your Skills: 7+ years in data engineering ...

Jira, Confluence, etc.) Desirable Experience Experience in Banking (essential focus area) Exposure to Model Context Protocol (MCP) Experience in regulated enterprise environments Understanding of MLOps/LLMOps practices Ability to contribute to ROI modelling, business cases, and AI value articulation Experience mentoring or leading delivery teams (Manager level) Role Focus ...

deploying production-grade AI systems using Azure, Databricks and Generative AI tooling Owning the implementation of ML pipelines, APIs and data integration workflows Enforcing MLOps best practices, coding standards, version control and performance optimisation Collaborating cross-functionally with data scientists, product managers, platform engineers, QA and audit professionals Mentoring junior ...

Experience working with major cloud platforms such as AWS, Azure, or GCP. Familiarity with containerisation and orchestration technologies (e.g. Docker, Kubernetes). Exposure to MLOps practices or deploying AI/ML models into production environments. Experience working in agile or fast-paced delivery teams . ...

such as GraphDB, Stardog, Neo4j, Amazon Neptune, or Blazegraph. Experience with embeddings, vector databases, RAG, LLM-based enrichment, or knowledge graph completion. Experience with MLOps tools such as Docker, Kubernetes, MLflow, Weights & Biases, Airflow, or similar. Experience with AWS, GCP, or Azure. Experience in construction, architecture, BIM, building materials, technical ...

model artifacts, and inference outputs. Maintain audit trails for model decisions, data access, and deployment history. Attributes Required Qualifications 4+ years of experience in MLOps, ML Engineering, DevOps, or a closely related infrastructure role. Strong proficiency in Python for ML pipeline development, tooling, and automation. Hands-on experience with ...

monitoring, logging and observability platforms • Strong troubleshooting and communication skills • Experience working with Kubernetes, CI/CD pipelines or distributed systems • Exposure to AI, MLOps or LLM-based systems would be beneficial Nice to have: • Experience with RAG pipelines or orchestration frameworks • Exposure to Databricks, MLflow or AI observability tooling ...

Unix environments, Git, and testing practices Understanding of data governance and security best practices Desirable Skills Experience using GPUs in cloud environments Knowledge of MLOps, CI/CD pipelines, and monitoring ML models Experience building APIs and working with modern DevOps practices Eligibility Requirements Due to the nature ...

engineering initiatives Mentor and support junior engineers within the team Contribute to engineering standards, reusable patterns, and AI best practices Help shape scalable MLOps and AI deployment approaches Drive high-quality engineering practices across testing, deployment, monitoring, and optimisation Tech environment Key technologies include: Python Azure Databricks Generative AI/ ...

recommendation systems Familiarity with scientific, biomedical, or scholarly datasets Experience with knowledge graphs, ontologies, or semantic enrichment systems Exposure to production ML systems and MLOps practices Publications or applied research contributions in NLP, IR, search, or generative AI Experience building AI systems in regulated, high-trust, or content-rich domains ...

analytics alongside AI solutions). Technical Scope Platform-agnostic engineering mindset; able to work across varied client stacks. Experience with cloud AI services and MLOps/LLMOps (e.g., Azure AI Foundry, AWS SageMaker and/or Bedrock). Strong software engineering practices: Python, APIs, containerisation, CI/CD, IaC, testing ...

into AI-led solutions Advise stakeholders on AI strategy, feasibility, and roadmap Leadership: Guide and mentor AI/engineering teams Set best practices across MLOps/LLMOps/AI governance Contribute to reusable frameworks and accelerators What youll need (must-have): Experience as an AI Architect/ML Architect/ ...

tools like Spark, Hive or Redshift A track record of leading cross-functional teams and communicating technical concepts to non-technical audiences Experience with MLOps practices - CI/CD, model monitoring, DevOps integration ADVERT DISCLAIMER Research indicates that men will apply to a role when they only meet ...

associated architecture patterns Experience designing and managing APIs including REST and GraphQL Strong understanding of microservices and serverless architectures Practical experience with DevOps and MLOps practices including CI/CD pipelines Knowledge of security frameworks, identity management and authentication standards Desirable Skills for the AI Solutions Architect: Experience with enterprise ...

automation workflows • Build scalable APIs, backend services, and integrations • Define and mature the organisation’s AI architecture and engineering standards • Implement robust DevOps/MLOps practices for AI systems • Mentor engineers and improve AI delivery capability across the team • Work closely with product and business stakeholders to shape ...

copilots/agents (e.g., vibe coding) to validate value and architectural fit Core Skills AI/ML and GenAI fundamentals (LLMs, RAG, AI agents, MLOps) Business consulting, problem framing, and architecture-to-value storytelling Program leadership and stakeholder management across product, engineering, and architecture teams Commercial acumen and deal shaping ...

Looking for experience with: ✔ Python ✔ PyTorch/TensorFlow/Scikit-learn ✔ Production ML systems ✔ AWS/GCP/Azure Bonus points for MLOps, signal processing, maritime or offshore energy experience. If interested, please apply or message directly. ...

product selling. Demonstrated success in selling: Generative AI and LLM-based enterprise solutions Predictive and prescriptive analytics Intelligent Automation (RPA + AI) Data Engineering, MLOps, and AI platforms Ability to articulate AI ethics, governance, security, and compliance considerations. Experience selling Managed AI Services and AI-as-a-Service models . ...

Experience with agent frameworks, tool-use planning and workflow orchestration Systems-level fluency across data pipelines, training infrastructure and inference (PyTorch, JAX, TensorFlow) Strong MLOps discipline: CI/CD for models, offline/online evaluation, safety and guardrails The ability to influence at exec level and mentor senior technical talent ...

focus include: Real-time sports insights & personalisation Computer vision & multimodal AI Live event detection & metadata generation Low-latency ML inference systems End-to-end MLOps & production ML Scalable cloud-native AI platforms What they’re looking for: Strong experience leading ML engineering initiatives in sports, media, streaming, or real-time ...

enterprise-scale operating models and shared services environments is beneficial. Required Skills AI & Agent Platforms: Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry Data & MLOps: Databricks, Azure SQL, ADLS, Azure AI Search Cloud & Integration: Microsoft Azure, API Management, Containers Identity & Security: Azure Entra ID, Key Vault, RBAC Observability & Governance: Logging ...

virtual assistants through advanced prompt engineering and agent orchestration 🔹 Integrate AI applications with SQL, NoSQL, Vector Databases, Knowledge Graphs, and third-party systems 🔹 Implement MLOps best practices and contribute to CI/CD pipelines using Docker, Kubernetes, and Cloud Platforms 🔹 Collaborate with Data Scientists, Architects, Product Managers, and Engineering teams … expertise in: Prompt Engineering Conversational AI NLP Applications AI Agent Development ✔ Experience building scalable APIs using FastAPI ✔ Strong understanding of: HTTP & gRPC Docker & Kubernetes MLOps & AI Deployment Cloud AI Services (AWS, Azure, or GCP) ✔ Experience deploying production-grade AI solutions on enterprise platforms ⭐ Nice to Have ✔ Experience with Vector Databases ...

particularly within the YOLO family. Familiarity with model optimization techniques such as quantization and pruning, and deployment frameworks like TensorRT and OpenVINO. Experience with MLOps tools and practices, including version control (Git), Docker, and CI/CD with GitHub Actions. Excellent problem-solving skills and the ability to perform ...

such as SuperSet, Tableau or PowerBI is a bonus) Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems Proven ability to create polished presentations and effectively communicate insights to customers ...

practices Developing long-term relationships with candidates from leading AI research labs and companies Typical Roles You’ll Recruit For Research Engineers Research Scientists MLOps Engineers Data Scientists AI/ML Engineers What We’re Looking For Proven experience in recruiting for Data, AI, or highly technical domains Strong track ...