1 to 25 of 34 MLOps Jobs in Central London

serving, versioning, and lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Databricks Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly ...

Design and implement Onsera's agentic AI platform – architect LLM/agent framework selection, standardized patterns for tools, memory, guardrails, evaluation, and observability Define MLOps protocols for agentic systems – environment separation, versioning of prompts, tools, and policies, cost controls, rate-limiting, and fail-safe mechanisms Bridge data science and platform ...

Microsoft AI Foundry or Ollama advantageous). Strong grasp of CI/CD, testing, version control, secure coding, and modern engineering workflows. Exposure to MLOps tools such as MLflow, Kubeflow, or Azure ML. ...

multi-supplier environment. Familiarity with data science tooling and terminology (Python, SQL, etc.) is desirable. Understanding of cloud platforms (Azure, AWS, GCP) and MLOps and DevOps practices. Demonstrable experience working as a Business Analyst in large complex organisations, preferably within a consultancy. Benefits: Hybrid working model allowing flexibility. Opportunity ...

skills and experience with ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch). Experience with model deployment, monitoring and ML pipelines (e.g. CI/CD, MLOps concepts). A collaborative mindset with strong communication skills and experience working in cross-functional teams. If this role looks of interest, apply below. ...

explain clearly to non-technical audiences DS background that has moved into AI engineering/LLM product delivery is ideal Bonus: Databricks, Azure, MLOps/CI-CD experience Interested? Please apply below. ...

data workflows 💬 Strong communication skills and a collaborative mindset ⭐ Big bonus points for: ❄️ Experience with Snowflake 🧱 Experience with Databricks ⚙️ Exposure to ML pipelines, MLOps, or production ML systems If you’re excited about building AI systems, learning fast, and growing your career in a supportive, high-impact environment ...

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 ...

human-in-the-loop review where needed. Ensure regulatory alignment (e.g., GDPR, ISO controls) and collaborate with risk, legal, and security for approvals. Define MLOps processes for versioning, evaluation, promotion, rollback, and monitoring (latency, cost, drift, hallucination rate, safety events). Instrument observability (logging, tracing, metrics) and error budgets; establish ...

MLOps Data Engineer Hybrid 2/3 days London Outside IR/35 Were looking for a Data Engineer with strong MLOps ownershipsomeone who builds reliable data pipelines and designs, runs, and improves ML pipelines in production. You wont be training models day-to-day like a Data Scientist; instead … packaging, deployment, and retraining Partner closely with Data Scientists to productionize models: standardise workflows, ensure reproducibility, and reduce time-to-production Build and maintain MLOps automation: CI/CD for ML, environment management, artefact handling, versioning of data/models/code Implement observability for ML systems: monitoring, alerting, logging ...

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 ...

SaaS architecture. Solid ETL, data processing, and feature engineering experience. Strong statistical and analytical capabilities. Experience in start-up or scale-up environments. Desirable MLOps tools (MLflow, Kubeflow, Sagemaker, etc.) Experience in PropTech or property data. Cloud experience (AWS/GCP/Azure). Docker/Kubernetes, CI/ ...

architectures . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ML models at scale. Experience moving LLM-based prototypes into production environments with thousands of users. Background in building internal tooling, CRM enhancements, or sales ...

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 . ...

platforms, frameworks, and libraries 📚 Extensive experience with end-to-end model design and deployment within cloud environments ☁️ A systems thinking approach 🌐, with passion for MLOps best practises 🌀 An engineer that can think in O(n) as much as plan the orchestration of their product. Solid understanding of data structures, data ...

globally. Key Responsibilities Research and develop state-of-the-art ML algorithms for network orchestration Build and manage ML training infrastructure using Kubernetes and MLOps tools Develop and maintain documentation for new algorithms and systems Integrate AI/ML solutions into the wider Spacetime platform Act as a technical expert ...

engineers, ML engineers, architects, and business teams to shape ML initiatives. Present insights clearly through strong data visualisation and storytelling. Uphold software engineering and MLOps best practices (testing, versioning, quality, automation). Contribute to governance, responsible model usage, and data quality standards. Mentor juniors and support code reviews. Required Experience ...

CUDA and optimising highly parallelised GPU-based computations are a plus Familiarity with the end-to-end supervised training of neural networks and accompanying MLOps ecosystem are a plus Familiarity with Django and related frameworks/tools Familiarity with other programming languages and frameworks At a personal level ...

coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming ...

quota selling UK apprenticeship standards (Digital, Data, Tech or Leadership). Data & AI Literacy: able to hold credible conversations on data analytics, data engineering, MLOps and emerging AI tooling. Consultative/MEDDIC Methodology: expert in discovery, ROI modelling, proposal crafting and multi‐stakeholder negotiation. Network: existing relationships with enterprise ...

statistics, machine learning, and deep learning. Experience with evaluation frameworks and observability tools. Contributions to open-source AI projects or published research. Familiarity with MLOps, model serving (vLLM, TGI), and infrastructure for AI at scale. Background in fine-tuning, RLHF, or working with open-weight models. ...

concepts to technical and non-technical stakeholders. Managing project delivery to ensure outcomes are on time, within budget and to quality standards. Applying MLOps practices to address risk and technical debt. Staying up to date with advancements in AI, agent architectures and emerging best practices. What youll bring Proven experience ...

simulation + tele‐op logs, version them, apply weak‐supervision labelling, curate balanced datasets, and auto‐surface fresh failure cases into retraining. Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‐time edge inference. We’re Looking For: 3+ years building deep‐learning systems ...

ongoing BAU support and maintenance of data structures, schema, reporting etc. Work with the broader Engineering community to develop the client's data and MLOps capability infrastructure Ensure data quality, governance, and compliance with internal and external standards. Monitor and troubleshoot data pipeline issues, ensuring reliability and accuracy. ...

want to work with the latest in LLMs, co-pilots, agentic workflows, RAGs , and more, while also applying real data science, ML, and MLOps skills in live enterprise environments. What You’ll Do: Work directly with enterprise clients to design and deploy custom AI agents Tackle complex business problems with ...