1 to 25 of 31 MLOps Jobs in Central London

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 . ...

solutions based on real user feedback and real-world constraints. Learn modern tooling and practices Gain hands-on experience with ML frameworks, cloud infrastructure, MLOps tools, and best practices for building scalable AI systems. Communicate clearly Translate technical findings into clear, structured insights for collaborators across technical and business teams. ...

Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If you have these skills and would like to find ...

ecosystem components including data lakes, data warehouses, data mesh architectures, and associated architectural patterns. Strong understanding of methodologies and principles of data science and MLOps, including model development, validation, and lifecycle management. Experience in data pipeline design, ETL/ELT processes, and data integration approaches and appreciation of trade-offs ...

architectural decisions that balance speed, quality, and regulatory compliance Also Valuable Experience with healthcare data interoperability (FHIR, HL7, DICOM) Exposure to ML model serving, MLOps pipelines, or ML frameworks (TensorFlow, PyTorch) Understanding of GDPR, HIPAA, or UK Data Protection Act compliance Experience with Infrastructure as Code (Terraform, CloudFormation ...

deal requirements into technical solutions. Support post‐merger integration (PMI) through AI‐enabled insights, reporting, and performance tracking. Deploy solutions into production using modern MLOps and cloud practices . Ensure models are explainable, auditable, and aligned with governance and regulatory requirements in transaction contexts. Contribute to AI strategy, architecture … Spark, Airflow or similar) LLMs, NLP, and document intelligence (e.g. RAG, embeddings) Experience with cloud platforms (AWS, Azure, or GCP). Understanding of MLOps , CI/CD, model monitoring, and governance. M&A/Transaction Experience Direct experience supporting M&A, private equity, corporate development, or transaction advisory . Proven ...

Senior ML/MLOps Engineer (MLflow) | Databricks | Azure) About Optima Partners We’re an advanced data & business consultancy helping major consumer brands transform through data-driven customer strategy, design, and engineering. Our clients include leading UK and global brands across financial services, retail, and more. Join a practitioner-led, fast … growing team delivering ML systems that actually make it into production. We’re growing our engineering team and looking for an MLOps Engineer who loves building real, production grade ML systems not just proof‐of‐concepts. If you enjoy working across the full ML lifecycle and have strong MLflow experience ...

product and systems thinking with a practical, impact-led mindset. Nice to Have AWS experience (e.g. SageMaker, Bedrock, Lambda, S3, Redshift). Familiarity with MLOps practices. Background in adtech, media, fraud, or adversarial systems. Why Join Work on technically challenging, high-scale AI problems. End-to-end ownership from experimentation ...

needed for this role: Expert AI/ML Skills Strong in both traditional ML and modern LLM/RAG/agentic workflows Production Deployment & MLOps Comfortable shipping scalable AI systems using APIs, microservices, Docker/Kubernetes, click apply for full job details ...

technical teams, with strong communication and collaboration skills. Awareness of data governance, secure handling of sensitive data, and regulatory considerations. Knowledge of MLOps/DevOps practices, including CI/CD pipelines for ML models. Understanding of reinforcement learning, multi-agent systems, or advanced optimization methods. Previous experience working in regulated ...

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 ...

including vector embeddings , rerankers , and data indexing in databases like MongoDB. Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization. Familiarity with MLOps principles and tools, including CI/CD with GitHub Actions . A strong interest in computer vision and an understanding of object detection models like ...

systems tailored to audit applications. Contribute to architectural decisions and solution governance. Write clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable … development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability. Cross-Disciplinary Collaboration: Work side-by-side with data scientists, product managers, platform engineers, and QA teams to align on technical requirements, delivery timelines, and integration plans. Provide hands-on contributions ...

preferred) and experience with modern AI/ML frameworks. Proven experience delivering AI solutions in complex or high‐security environments. Desirable Skills Experience with MLOps, LLMOps, or production‐grade AI deployments. Knowledge of vector databases, RAG, and prompt engineering techniques. Exposure to government, defence, or national security domains. Who This ...

team environment Nice to Have Background in bioinformatics, computational biology, or life sciences Experience with drug discovery, protein modelling, or genomics pipelines Familiarity with MLOps, CI/CD, and scalable cloud infrastructure Exposure to graph-based models, transformers, or multimodal learning Experience in an early-stage startup or fast-scaling ...

your own on architectural trade-offs. You're fluent enough in the modern data and AI stack - Python, cloud-native services, event-driven architectures, MLOps tooling, LLM evaluation - to make informed product calls without relying on engineering to tell you what's possible. Salary and equity calibrated to the seed ...

requires someone who can engage with business stakeholders, design AI-driven architectures, and also contribute hands-on to development and deployment, particularly in AI MLOps environments. This is not a pure data scientist role or a pure BA role but a design + build + deploy role within Payments transformation … embedding AI into payments systems Work with data pipelines (real-time + batch) Implement data preprocessing, feature engineering, and model evaluation 4. AI MLOps & Deployment Set up and manage ML lifecycle using MLOps frameworks Implement: Model versioning CI/CD pipelines Monitoring & drift detection Governance and audit controls Ensure production ...

Inside IR35 contract | 3-6 month 1-2 days onsite requirement London or Birmingham We are seeking an experienced MLOps Engineer with a strong background in DevOps, Data Science, or Machine Learning Engineering, who has hands-on experience productionising ML models. The focus of the role is building and enabling … itself. Candidates must have deep MLflow experience and proven delivery in real-world client settings. Key Responsibilities Design, build, and maintain end-to-end MLOps environments to support model training, tracking, deployment, and monitoring Implement MLflow for: Experiment tracking; Model registry; Model versioning and lifecycle management Enable model deployment into ...

pure manager) Nice to have FMCG/retail/commercial analytics experience (NIQ/Circana a plus) dbt/semantic layer design MLOps, evaluation & observability tooling Background in consulting or data science roles, now looking to own a product end-to-end Why this role is different Build real 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. ...

predictive analytics — helping the world's largest employers find the right people, faster and fairer. But we're not done. Not even close. Role: MLOps Engineer Location: Remote Industry: Technology/AI & ML Infrastructure Job Function: MLOps/ML Platform Engineering Role Overview: We are hiring an MLOps Engineer ...

impact, working with diverse data types - including text, images, audio, video, and geospatial data - while applying cutting-edge methods in AI, machine learning, and MLOps/LLMOps practices. You'll have the opportunity to: Work alongside leading data scientists, ML engineers, and AI researchers on national security projects Design, develop … traditional ML use cases and GenAI/LLM applications Explore and implement ML and LLM models on complex, multi-modal datasets Apply modern MLOps/LLMOps practices, including experiment tracking, versioning, and deployment on cloud platforms Influence technical direction and best practice in ML and AI engineering Mentor and support ...

discovered and developed. We’re looking for senior candidates with deep expertise in: • Deep learning and modern ML systems • Distributed training and GPU infrastructure • MLOps, deployment, and reliability at scale • Biomedical, genomics, or drug discovery ML Requirements 7+ years relevant post PhD experience Experience productionising foundation models and model components ...

design, build and deploy advanced NLP and LLM-based solutions, taking models from research through to production. You’ll work closely with AI, data, MLOps and product teams to translate business and regulatory requirements into scalable, reliable AI systems. This is a hands-on role for someone who enjoys owning … data preprocessing pipelines Monitoring, optimising and maintaining deployed models for performance, cost and reliability Implementing explainability, fairness and bias-mitigation strategies Collaborating on MLOps pipelines, CI/CD workflows and production deployments Mentoring junior engineers and promoting best practices across the team Staying current with advances ...

resource plans, timelines, and risk frameworks 🏗 Design AI Architectures Translate requirements into scalable AI/ML solutions Design architectures covering: Model development Data pipelines MLOps and monitoring Cloud integration (Azure, AWS, or GCP) Validate feasibility with engineering and delivery teams ✍️ Lead Tender & Bid Responses Own technical sections of AI RFPs … capability in scoping AI/ML programmes and estimating effort Deep understanding of: Machine learning (supervised & unsupervised) Generative AI & LLMs Embeddings, vector databases, RAG MLOps and model lifecycle management Experience with platforms such as: Azure ML, AWS SageMaker, Google Vertex AI Databricks, LangChain, Hugging Face Ability to develop architecture artefacts ...