13 of 13 Remote/Hybrid 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 ...

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 ...

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 ...

LLMs and RAG architectures. Python: Strong proficiency alongside PySpark for data engineering. Azure: Deep familiarity with native tools (AI Search, Document Intelligence). MLOps: Understanding of LLMOps frameworks for production deployment. 6 Months Remote Contract | £600 a day inside IR35 | Active Security Clearance Are you a seasoned technical leader with ...

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 ...

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 ...

infrastructure every pricing professional aspires to work with: High-quality, accessible data A fast, flexible rating algorithm deploy changes in hours Machine Learning Operations (MLOps) that enable fast, transparent, and controlled model development An operating model that gives complete autonomy to pricing professionals to dream up an idea ...

biological plausibility, calibration, and model reliability Collaborating closely with computational biologists and research scientists to integrate models into discovery workflows Driving best practices across MLOps, experimentation infrastructure, and model deployment What They're Looking For Essential 5+ years experience building advanced machine learning systems in production Strong background in deep ...

solutions from development through to deployment and monitoring * Building scalable Generative AI and Agentic AI solutions, including RAG pipelines and orchestration frameworks * Implementing MLOps frameworks, governance and best practices * Translating business requirements into cloud-native AI and data architectures across Azure, AWS and GCP * Collaborating with technical and non-technical … stakeholders to deliver measurable business value * Supporting innovation initiatives, reusable assets, thought leadership and client proposals Candidates should have strong experience in AI Engineering, MLOps and cloud-native AI platforms, alongside hands-on knowledge of technologies such as LangChain, LlamaIndex, MLflow, Kubernetes, Docker and CI/CD tooling. Applicants will ...

Entrust Identity Verification — Powering the systems behind digital trust. At Entrust, identity is no longer a compliance checkbox—it’s a real-time product problem shaped by machine learning, adversarial behavior, and high-stakes decisions. ...