201 to 225 of 299 MLOps Jobs in London

and deployment workflows Analytics & Reporting – enabling insights through dashboards, reporting tools, and data aggregation Automation – building scripts and utilities to streamline and optimize operations Data Engineering/DevOps/MLOps – contributing to data infrastructure, deployment pipelines, and scalable systems Must-Have Skills: Strong programming skills in Python with ability to write modular and maintainable code Solid understanding of data structures … or containerization (Docker) Awareness of analytics tools (e.g., Power BI, Tableau), dashboards, or reporting pipelines Experience with automation scripts, data wrangling, or internal tooling Basic understanding of DevOps or MLOps workflows and CI/CD pipelines Eligibility BE/B.Tech or equivalent –2025 pass-outs Academic background in CS/IT/ECE/EE/Math or other technical More ❯

and deployment workflows Analytics & Reporting – enabling insights through dashboards, reporting tools, and data aggregation Automation – building scripts and utilities to streamline and optimize operations Data Engineering/DevOps/MLOps – contributing to data infrastructure, deployment pipelines, and scalable systems Must-Have Skills: Strong programming skills in Python with ability to write modular and maintainable code Solid understanding of data structures … or containerization (Docker) Awareness of analytics tools (e.g., Power BI, Tableau), dashboards, or reporting pipelines Experience with automation scripts, data wrangling, or internal tooling Basic understanding of DevOps or MLOps workflows and CI/CD pipelines Eligibility BE/B.Tech or equivalent –2025 pass-outs Academic background in CS/IT/ECE/EE/Math or other technical More ❯

use cases, and translate business needs into AI/ML solutions. Develop, test, and optimize AI models, ensuring they align with business goals and regulatory requirements. Work closely with MLOps engineers and the wider Tech and Data teams to deploy production-ready solutions. Stay ahead of industry trends, particularly in Data Science, NLP, and GenAi advancements, and share insights across … NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks for building end-to-end ML pipelines. Proven ability to lead and deliver data science projects in an agile environment. Excellent stakeholder management and communication skills to bridge the More ❯

advanced analytics techniques, machine learning approaches, and modern pricing tools. ML Engineering Integration: Partner with ML Engineering to elevate model sophistication, overseeing integration with Radar API and ensuring smooth MLOps deployment pipelines. Leadership & Mentoring: Support and mentor junior analysts, sharing knowledge and promoting best practices across the team. Who are you: We know we have high expectations, so please don … and deliver meaningful change end-to-end Excellent communication and stakeholder skills, with the ability to present technical insights clearly to non-technical audiences Nice-to-have Familiarity with MLOps and development best practice, including production-grade model design and deployment, version control (e.g. Git), code reviews, CI/CD pipelines, unit testing, and collaborative workflows such as Agile. Experience More ❯

Job Description Depop is looking for a versatile Senior Machine Learning Scientist to join our Search & Ranking team in the UK. As part of the team, you will work alongside a Product Manager, Backend Engineers, and other ML Scientists, playing More ❯

plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Required Skills Exceptional collaboration and relationship building skills Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces Resilient problem solving and critical thinking skills Ability to More ❯

plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Required Skills Exceptional collaboration and relationship building skills Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces Resilient problem solving and critical thinking skills Ability to More ❯

ML teams in high-velocity environments. Deep knowledge of modern ML (supervised, unsupervised, generative, self-supervised learning, etc.). Strong understanding of ML systems at scale: inference pipelines, observability, MLOps, data pipelines, etc. Background in building ML for real-world infra, distributed systems, or low-latency environments is a big plus. Confident working at both strategic and technical depth, exec More ❯

leading enterprises deploy cutting-edge AI agents. The ideal candidate will bring a blend of: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: up-to-speed with the latest AI tools and active (daily) leverage of the same (co-pilots, MCPs, agentic workflows, RAGs, LLMs) - we appreciate these are new and More ❯

leads to ensure consistency and quality Eligible for UK Government Security Clearance (SC minimum, DV preferred) Desirable Experience in client-facing roles or consulting Familiarity with LLMs, AI agents, MLOps or containerised deployments in classified settings Understanding of AI governance, ISO 42001, or model assurance frameworks More ❯

leads to ensure consistency and quality Eligible for UK Government Security Clearance (SC minimum, DV preferred) Desirable Experience in client-facing roles or consulting Familiarity with LLMs, AI agents, MLOps or containerised deployments in classified settings Understanding of AI governance, ISO 42001, or model assurance frameworks More ❯

opportunities and technologies. Who we're looking for An experienced technology leader with a track record of successfully leading AI/ML strategy and project delivery. Strong understanding of MLOps, with experience deploying commercially valuable AI applications in financial services. Experience leading full-stack technology teams, with a solid grasp of systems architecture and engineering fundamentals. Knowledge of the financial More ❯

or prototypes at high velocity, ideally in startup or research contexts where speed and adaptability are paramount. Deep expertise in Generative AI, multi-agent systems, LLMs, end-to-end MLOps, and AI infrastructure. Exposure to Deep Learning, Reinforcement Learning, federated learning, AI evaluation or ML fundamentals is highly beneficial. Active interest and awareness of SOTA in multi-agent systems, collective More ❯

vision to build systems that are faster, more thorough and more accurate than humans. Evals: Build benchmarks, evaluate backtests and analyse results to quantify our performance and prevent regressions. MLOps: Ensure that we maintain good practices around collecting and managing datasets, backtests and benchmarks to to maximise development velocity Prompt Engineering: Develop and test prompts to optimise model performance and More ❯

NoSQL) Practical experience in establishing data governance frameworks, data quality initiatives, and Master Data Management solutions Understanding of data requirements for machine learning, including feature stores, data versioning, and MLOps principles Familiarity with common retail data domains (e.g., customer, sales, inventory, product, supply chain, marketing data) Ability to translate complex technical concepts into clear business terms and effectively communicate with More ❯

NoSQL) Practical experience in establishing data governance frameworks, data quality initiatives, and Master Data Management solutions Understanding of data requirements for machine learning, including feature stores, data versioning, and MLOps principles Familiarity with common retail data domains (e.g., customer, sales, inventory, product, supply chain, marketing data) Ability to translate complex technical concepts into clear business terms and effectively communicate with More ❯

NoSQL) Practical experience in establishing data governance frameworks, data quality initiatives, and Master Data Management solutions Understanding of data requirements for machine learning, including feature stores, data versioning, and MLOps principles Familiarity with common retail data domains (e.g., customer, sales, inventory, product, supply chain, marketing data) Ability to translate complex technical concepts into clear business terms and effectively communicate with More ❯

define AI use cases, and iterate quickly on prototypes. Integrate complementary AI capabilities-such as voice processing, computer vision, and NLP-into customer-facing and internal tools. Collaborate with MLOps and platform engineers to ensure models are deployed, monitored, and iterated in production environments. Maintain clear documentation for AI systems, APIs, and workflows. Stay on top of emerging AI frameworks … using containerised solutions (Docker, Kubernetes) and frameworks like BentoML or equivalent. Familiarity with vector databases and retrieval pipelines for RAG architectures. Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps tooling (MLflow, Kubeflow, or similar). Familiarity with voice-to-text, IVR, and/or computer vision systems is a plus. Strong understanding of software engineering best practices-testing, CI More ❯

experiment, ship, and see your work reflected in customers' financial freedom. At Updraft, you'll help build a fairer credit system. The Role We're looking for an experienced MLOps Engineer for a 3-month contract to lead the development of our ML deployment, testing, monitoring, and feature engineering pipelines . You'll be responsible for establishing best practices and … learning workflows from training to deployment and beyond. The role could be extended to a longer DevOps contract. What You'll Do - Design and build an end-to-end MLOps pipeline using AWS , with a strong focus on SageMaker for training, deployment, and hosting. - Integrate and operationalize MLflow for model versioning, experiment tracking, and reproducibility. - Architect and implement a feature … workflows (training, evaluation, deployment), integrating with tools such as GitHub Actions , CodePipeline , or Jenkins . - Create internal documentation and onboarding guides for engineering and data teams to adopt new MLOps practices. What We're Looking For - 3+ years of experience in MLOps, DevOps, or ML infrastructure roles. - Deep familiarity with AWS services , especially SageMaker , S3, Lambda, CloudWatch, IAM, and optionally More ❯

Job Description Depop is looking for a versatile Senior Machine Learning Scientist to join our Recommendations team in the UK. As part of the team, you will work alongside a Product Manager, Backend Engineers, and other ML Scientists, playing a More ❯

As Opus 2 continues to embed AI into our platform, we need robust, scalable data systems that power intelligent workflows and support advanced model behaviours. Were looking for an MLOps Engineer to build and maintain the infrastructure that powers our AI systems. You will be the bridge between our data science and engineering teams, ensuring that our machine learning models … is passionate about building robust, scalable, and automated systems for machine learning, particularly for cutting-edge LLM-powered applications. What you'll be doing Design, build, and maintain our MLOps infrastructure, establishing best practices for CI/CD for machine learning, including model testing, versioning, and deployment. Develop and manage scalable and automated pipelines for training, evaluating, and deploying machine … strategy and roadmap by providing expertise on the operational feasibility and scalability of proposed AI features. Collaborate closely with Principal Data Scientists and Principal Engineers to ensure that the MLOps framework supports the full scope of AI workflows and model interaction layers. What excites us? Weve moved past experimentation. We have live AI features and a strong pipeline of customers More ❯

with people who are passionate about data and its ability to empower and improve lives. Work with cross-functional teams to deliver production level ML/AI solutions. Implement MLOps with a focus on versioning and data security. Champion Machine Learning across the business. Mentor junior members of the team. Profit share bonus. Skills and Experience Python. MLOps. Strong communication More ❯

plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Exceptional collaboration and relationship building skills More ❯

plus Demonstrated experience building APIs to support analytics/research/actuarial functions in an insurance company setting Experience with cloud technologies like Snowflake and Databricks Familiarity with the MLOps framework Exceptional collaboration and relationship building skills More ❯

prompt practices. Proven change leadership: you have driven ≥50% adoption with training and comms. Governance mindset: you have designed guardrails that pass risk and legal review. Working grasp of MLOps/GenAIOps (CI/CD, model registry, data lineage, evaluation). Clear communicator: you can brief boards and coach non-technical teams. Comfortable in a matrix: you align marketing, data More ❯