201 to 225 of 341 MLOps Jobs in the UK

these AI products. You will be building tools for model training and evaluation, collaborating with Data Scientists and Engineers to get these solutions into production, and driving improvements in MLOps processes. You'll have worked as a Machine Learning Engineer or Data Scientist in the past, ideally centred around a software product, and have solid Python coding skills, and expertise More ❯

these AI products. You will be building tools for model training and evaluation, collaborating with Data Scientists and Engineers to get these solutions into production, and driving improvements in MLOps processes. Youll have worked as a Machine Learning Engineer or Data Scientist in the past, ideally centred around a software product, and have solid Python coding skills, and expertise with More ❯

of machine learning, creating tools for model training and evaluation that power transformative healthcare applications. Collaborating closely with Data Scientists and Engineers, youll produce advanced AI solutions while optimizing MLOps processes to drive efficiency and impact. The ideal candidate will bring experience as a Machine Learning Engineer or Data Scientist, preferably within the healthcare, biotech, or pharmaceutical space. Strong Python More ❯

ready. Key Responsibilities Build machine learning models for forecasting, propensity scoring, and segmentation Own workflows from data wrangling and feature engineering through to deployment and monitoring Operationalise models using MLOps tools in a cloud-native environment Architect datasets by merging structured and semi-structured data Work closely with engineers, product managers, and clients to align models with business needs Present More ❯

ready. Key Responsibilities Build machine learning models for forecasting, propensity scoring, and segmentation Own workflows from data wrangling and feature engineering through to deployment and monitoring Operationalise models using MLOps tools in a cloud-native environment Architect datasets by merging structured and semi-structured data Work closely with engineers, product managers, and clients to align models with business needs Present More ❯

assess and onboard new AI systems. - Evaluate solutions for compliance with internal policies and external regulations. Security & DevSecOps Integration: - Integrate AI security controls into CI/CD pipelines and MLOps workflows. - Monitor AI systems using Azure Monitor and Application Insights. Policy Implementation & Regulatory Alignment: - Translate regulatory requirements into actionable engineering guidelines. - Ensure compliance with transparency, data minimization, and incident response More ❯

assess and onboard new AI systems. - Evaluate solutions for compliance with internal policies and external regulations. Security & DevSecOps Integration: - Integrate AI security controls into CI/CD pipelines and MLOps workflows. - Monitor AI systems using Azure Monitor and Application Insights. Policy Implementation & Regulatory Alignment: - Translate regulatory requirements into actionable engineering guidelines. - Ensure compliance with transparency, data minimization, and incident response More ❯

your AI field. • You have a publication record. •You have a strong interest in fine-tuning and using language models for applications. • You are able to navigate the full MLOps technical stack, with a focus on architecture development and model evaluation and usage • You have experience in Audio/Speech experience - audio input/out, NLP etc Note that this More ❯

cross-functional teams Passionate about solving complex and challenging data problems Experience in designing and conducting A/B experiments Nice to have Experience with recommendation systems Familiarity with MLOps tools/practices Experience in consumer-facing mobile-first products Why join Muzz? We're a profitable Consumer Tech startup, backed by Y Combinator (S17) and based in London . More ❯

everything from lit. review, through training and evaluation, to optimisation and deployment. Design and develop robust and efficient C Rust software for multi-sensor, multi-target tracking & estimation problems MLOPS - build and maintain automated, scalable infrastructure to manage our data and run our experiments Design experiments, data collection efforts, and curate training/evaluation sets to develop insights both for More ❯

Press Tab to Move to Skip to Content Link • Job Title: Senior MLOps/GenAI Infrastructure Engineer • Location: London/Salford/Glasgow/Newcastle/Cardiff (This is a hybrid role and the successful candidate will balance office working with home working) • Band: D • Salary: up to £59,600 - £69,800 (The expected salary range for this role reflects … modern digital ecosystem using exciting technologies and do the best work of their careers. Your Key Responsibilities And Impact Designing, developing, and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK … and knowledge-sharing through comprehensive documentation, technical deep dives, brown bag sessions, internal workshops, and active mentorship of team members. Your Skills And Experience Extensive experience of DevOps/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services 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 ❯

we looking for? Good experience working with Python & SQL Domain knowledge in customer & marketing - LTV, churn, segmentation, etc. Ability to build machine learning models in Python Production & deployment skills, MLOps Candidates must be based in the UK. Unfortunately we cannot offer sponsorship for this hire. Interested? Apply More ❯

we looking for? Good experience working with Python & SQL Domain knowledge in customer & marketing - LTV, churn, segmentation, etc. Ability to build machine learning models in Python Production & deployment skills, MLOps Candidates must be based in the UK. Unfortunately we cannot offer sponsorship for this hire. Interested? Apply 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 ❯

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 ❯

AI/ML models. The ideal candidate will have deep expertise in cloud technologies (Azure), Infrastructure as Code (IaC), container orchestration, and CI/CD pipelines. An understanding of MLOps and data pipeline tools is also essential for integrating with our AI components. Core Responsibilities Cloud Platform & Infrastructure Management Design, implement, and manage secure and high-performance cloud infrastructure on … end and back-end services. Implement monitoring, logging, and alerting solutions to ensure the health and performance of our platform. Promote a culture of automation across the development lifecycle. MLOps and Data Pipeline Integration Collaborate with data scientists and engineers to support the operationalization of machine learning models. Possess a strong understanding of data pipeline orchestration tools such as Apache … on experience with Kubernetes for container orchestration in a production environment. Experience with building and managing CI/CD pipelines (e.g., Jenkins, GitHub Actions, Azure DevOps). Familiarity with MLOps practices and tools including Apache Airflow is a significant plus. Technical Skills: Proficiency in programming languages such as Bash and Python Strong understanding of version control systems (e.g., Git). More ❯

insights and enhance engagement. Lead the development, evaluation, and monitoring of models (LLMs, predictive/classification, agentic workflows), ensuring security and compliance standards are met. Implement best practices for MLOps, including CI/CD, automated testing, model versioning, and data validation. Architect integrations with vector databases, cloud platforms, and retrieval-augmented generation systems. Qualifications: 3+ years of experience delivering full … Experience with frontend frameworks: React, Vue, or Angular. Hands-on experience building and scaling ML models (LLMs, NLP, classification) and deploying them as APIs/services. Strong skills in MLOps: containerisation (Docker, Kubernetes), cloud deployment (AWS, GCP, Azure), and CI/CD pipelines. Experience with prompt engineering, LLM evaluation, and vector databases (Pinecone, Weaviate, FAISS). Excellent communication skills and More ❯