1 to 25 of 28 Permanent MLOps Jobs in the South East

familiar with process management tools such as JIRA, Target process, Trello or similar Nice to Have: ● Familiarity with data security, privacy, and compliance frameworks ● Exposure to machine learning pipelines, MLOps, or AI-driven data products ● Experience with big data platforms and technologies such as EMR, Databricks, Kafka, Spark ● Exposure to AI/ML concepts and collaboration with data science or More ❯

principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling and insurance are a plus. Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc are desirable We’ll help you gain Experience working in a high-performance environment where More ❯

to strengthen our Systematic Research team, we are looking for a London based: Quantitative Analyst We are seeking a hands on quantitative researcher with strong software/DevOps/MLOps capability to develop, productionise, and scale systematic investment models and sustainability analytics. You will own the end to end research to production lifecycle : automating data operations, building and validating quant More ❯

real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯

Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the world designs More ❯

Engineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's reinventing how the world designs More ❯

with Front end Frameworks such as Angular, for integration of AI-powered applications Experience with graph databases and knowledge graphs (Neo4j) for knowledge graphs and tool routing. Cloud deployment & MLOps Production deployments on Azure (AKS/ACI/Functions), CI/CD, and Infrastructure as Code (Bicep/Terraform). Data & Information Management Experience with relational/semi-structured database More ❯

pragmatic mindset - able to balance innovation with execution. Nice-to-haves: Experience leading platform or DevOps product teams in life sciences, research, or AI-driven organisations . Familiarity with MLOps, GenAI, and large-scale compute orchestration . Background in computer science, engineering, or a related technical discipline. Package & Benefits: Base salary up to £145,000 . Car allowance , 18% bonus More ❯

for security clearance. Desirable Skills, but not essential: Proficiency in Arcade scripting across ESRI runtime environments. Familiarity with the Microsoft Azure cloud platform, including data and AI services, and MLOps Knowledge of geospatial data warehousing and analytics. Familiarity with leading AI/ML platforms and libraries Experience building and scheduling ETL workflows. Knowledge of spatial data management and geospatial queries. More ❯

Experience integrating AI models into production systems using GCP, AWS, or Azure. Familiarity with vector databases, embedding models, or retrieval-augmented generation (RAG). Knowledge of Docker, Airflow, or MLOps pipelines. Strong understanding of AI ethics, data privacy, and responsible model deployment. TO BE CONSIDERED... Please either apply online or email me directly at .By applying for this role, you More ❯

ML models. Partner with data 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 You'll need: Strong Python More ❯

enable adoption and application of validated models. Work as part of a fast-paced, agile development team , identifying and prioritizing opportunities to deliver new capabilities. Build and maintain robust MLOps pipelines for scalable, reproducible, and automated model development, deployment, and monitoring. Leverage tools such as Airflow for workflow orchestration and MLflow for experiment tracking, model registry, and lifecycle management, ensuring More ❯

strategic decision-making on technology and architecture to ensure scalable and cost-effective solutions. Driving the development of machine learning models, pipelines, and tooling, with a strong emphasis on MLOps best practices. Acting as a subject matter expert internally and externally, including with key customer stakeholders. Translating business requirements into robust technical solutions, ensuring alignment across teams. Promoting strong data More ❯

+ 10–20% bonus (linked to MVP pilot) Location: Slough (Hybrid - 2+ days/week) Stack: Python, LangChain, Semantic Kernel, vector DBs, Azure AI/MLOps Visa: No sponsorship available Interested? Please apply below. More ❯

seek an adept expert to contribute significantly to our R&D team, bridging machine learning engineering with applied data science. You'll improve and manage our Machine Learning Operations (MLOps) on Azure, and participate in creating, assessing, and advancing various machine learning models and AI systems. Collaborate extensively with scientific and operational teams to guarantee the robustness, scalability, and reliability … informed decision-making and boost innovation. Help our CDMO's mission by turning research insights into practical solutions efficiently. Key responsibilities: Compose, construct, and uphold resilient machine learning operations (MLOps) pipelines that facilitate the complete lifecycle of AI models—from creation to implementation and supervision. Guarantee the successful deployment of machine learning and large language models (LLMs) in practical operational … interpret, share, and act on. Key requirements: MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine More ❯

stories, change requests, and screen designs. A background as a Business Analyst is preferred. Experience in workforce management, scheduling, HR tech, optimisation domains, AI/ML productisation, LLM integration, MLOps, or enterprise integration standards (ETL, REST APIs, webhooks, event streaming) is a bonus. At the centre of the company's culture is freedom and openness which takes a lot of More ❯

and vector search architectures Ability to build autonomous agents that interact with APIs, fetch public data and trigger external actions Experience deploying AI solutions on Azure Strong understanding of MLOps, data engineering and model life cycle management Experience embedding AI features into a SaaS or operational technology platform Experience working in the manufacturing industry or with manufacturing, supply chain or More ❯

and vector search architectures Ability to build autonomous agents that interact with APIs, fetch public data and trigger external actions Experience deploying AI solutions on Azure Strong understanding of MLOps, data engineering and model lifecycle management Experience embedding AI features into a SaaS or operational technology platform Experience working in the manufacturing industry or with manufacturing, supply chain or inventory More ❯

Data Science Engineer - MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL We are actively working with a global law firm who are actively looking to bolster their IT team as they undergo a global-scale cloud transformation. At present they are looking to take on a new Data Science Engineer (MLOPS, Machine Learning … tier global law firm who have a long-stream of projects in the pipeline alongside a diverse and collaborative team environment. To be considered for this Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) role, it's ideal you have: Ideal but not required law firm experience 2-4 years … science and AI solutions end-to-end, from design and development through testing, release, monitoring, and support. Operationalize models with CI/CD pipelines, automated testing, and monitoring, applying MLOps practices such as versioning, retraining, and drift detection (tools: MLflow, Azure ML, Databricks) Leverage both open-source frameworks (LangChain, Hugging Face, etc.) and enterprise platforms (Azure OpenAI, Databricks, etc.) to More ❯

which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEO We are a dynamic team of specialists in Data Science, Data Engineering, and MLOps, dedicated to delivering cutting-edge AI solutions within secure government and defence environments. Join us to be part of an inclusive and collaborative environment where innovation thrives, and continuous learning More ❯

Scientists, Data Engineers, and DevSecOps teams , building automation pipelines that accelerate model development and deployment across distributed, cloud-native systems. Key Responsibilities Design, implement, and maintain end-to-end MLOps pipelines for model training, validation, deployment, and monitoring. Develop and automate workflows using Terraform, Kubernetes, Docker , and CI/CD toolchains (GitHub Actions, Jenkins, Argo, etc.). Manage scalable cloud … pipelines. Contribute to the development of a modular, reusable ML platform architecture supporting multi-modal data (genomic, clinical, imaging, etc.). Essential Skills and Experience Proven experience as an MLOps Engineer, Platform Engineer, or DevOps Engineer supporting ML or data science teams. Strong hands-on experience with containerization (Docker) and orchestration (Kubernetes) . Expertise in Terraform , Infrastructure as Code (IaC … Solid understanding of CI/CD pipelines and automated testing frameworks. Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn. Familiarity with MLflow, Kubeflow, DVC, or similar MLOps tools . Understanding of cloud security principles , IAM, and networking best practices. Proficiency in Python and Bash scripting for automation and tooling development. Version control with Git , and collaborative development More ❯

AI Engineer Up to £90,000 Salary Southern England x2 days per month OVERVIEW Xcede’s Data-driven Insurance client with an excellent Data Science, ML Engineering and MLOps team is hiring for an AI Engineer to join their AI unit. The organisation have been building commercially successful Data Science products for years, and are now pushing further into Generative … deployed machine learning models in production. Excellent use of Python Particular experience in NLP, LLMs, and RAGs are highly prized given the focus on these projects. CI/CD & MLOps experience is valued Databricks experience is valued If this role interests you and you would like to find out more, please apply here or contact us via niall.wharton@Xcede.com (feel More ❯

Solutions Architect - DevOps/DevSecOps/MLOps Solutions Architect UNITED KINGDOM DevOps Presales Engineer - LONDON - UNITED KINGDOM Salary: £160,000 (80/20 split) Remote Status: Hybrid - 3 days/week in LONDON office Job Description: We are looking for a DevOps Presales Engineer for our client, a market leader in DevOps, DevSecOps, and MLOps.This is a company trusted by … at industry events and conferences Train customers and community members on product capabilities Feed frontline insights back to the company to shape the product roadmap Stay ahead of DevOps & MLOps trends and bring that expertise to every customer conversation This is not a back-office DevOps role. You'll be front and centre in the sales process - a trusted technical More ❯

business needs from manufacturing, supply chain, engineering, and quality into actionable product requirements. Lead products from concept prototype production, ensuring scalability, performance, and regulatory alignment. Establish agile, DataOps, and MLOps practices to accelerate deployment of analytics and AI solutions. Guide the integration of operational data across ecosystems (MES, LIMS, ERP, QMS, plant-level data, SCADA, IoT, cloud). Track and … Deep domain expertise in global pharma, biopharma, or large-scale manufacturing/supply chain. Strong technical fluency: Data engineering & pipelines Cloud platforms Data science & AI/ML product delivery MLOps/DataOps principles Skilled at influencing product direction across cross-functional, multi-region teams. A strategic thinker capable of shaping long-term transformation while executing fast. Comfortable in complex, regulated More ❯

productionise both real-time and batch models. Tackle traditional tech challenges with fresh thinking and creative collaboration, driving continuous improvement. Design and implement AI/ML solutions with best MLOps/LLMOps practice that meet demanding performance and functionality standards. Lead the way in developing streamlined operational processes, ensuring smooth deployment, monitoring, and governance of models. Write clean, well-documented … productionise both real-time and batch models. Tackle traditional tech challenges with fresh thinking and creative collaboration, driving continuous improvement. Design and implement AI/ML solutions with best MLOps/LLMOps practice that meet demanding performance and functionality standards. Lead the way in developing streamlined operational processes, ensuring smooth deployment, monitoring, and governance of models. Write clean, well-documented More ❯