1 to 25 of 104 MLOps Jobs in the South East

LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). • Familiarity with on-device or edge-AI deployments (e.g., TensorFlow Lite, ONNX, mobile/embedded inference). • Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. • Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL More ❯

testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organizational skills to our team and help us drive innovation and excellence. This is a flexible … Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic … services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic More ❯

measurement. Collaborative Development: Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new More ❯

in structured data querying and other business-specific applications Integrate LLMs with structured data systems (e.g., SQL databases, BigQuery, GCS) to enable natural language querying and advanced analytics. Implementing MLOps/LLMOps pipelines for deploying LLMs in production, monitoring their performance, and ensuring scalability. Evaluating LLM performance, optimising hyperparameters, and ensuring alignment with business objectives. Develop and maintain data integration … LangGraph, including prompt engineering, fine-tuning, and workflow orchestration. Skilled in integrating LLMs with structured data systems (e.g., SQL databases, BigQuery) to enable natural language querying and advanced analytics. MLOps/LLMOps Proficient in designing and implementing MLOps/LLMOps pipelines for model deployment, monitoring, version control, and CI/CD workflows. Strong understanding of model performance evaluation, hyperparameter tuning More ❯

or GCP. ● Experience with Agile development methodologies. ● A strong understanding of ethical considerations in AI/ML. Preferred Qualifications: ○ Experience with deep learning and natural language processing. ○ Experience with MLOps and DevOps practices. ○ Experience with financial regulations and compliance requirements. ○ Degree in Computer Science, Data Science, or a related field. More ❯

team helping to 'walk in the shoes' of application teams as well as operational engineering teams. Communicate progress, results, and insights to management and other stakeholders. Strong understanding of MLops principles and practices. Daily/Monthly Responsibilities Build and run responsibilities for GenAI ensuring robust support folding into standard incident processes as the products mature. Help work with distributed teams … and LLMs. An overall 8+ years of experience as Software Engineer. Proficiency in programming languages such as Python, TensorFlow, PyTorch, and other AI/ML frameworks. Strong understanding of MLops principles and practices. Ability to design and implement complex ML systems. Strong understanding of neural networks, natural language processing (NLP), computer vision, and other AI domains. Experience with cloud platforms More ❯

machine learning lifecycle, designing sophisticated models, experimenting with cutting edge techniques and building robust, production-ready pipelines. You will also contribute to the technical architecture, champion best practices in MLOps, and guide the strategic direction of our AI capabilities. This is a hands-on role for someone who enjoys both deep technical work and cross-functional collaboration—driving forward innovation More ❯

tuning, and workflow orchestration. Skilled in integrating LLMs with structured data systems (e.g., SQL databases, BigQuery) to enable natural language querying and advanced analytics. Proficient in designing and implementing MLOps/LLMOps pipelines for model deployment, monitoring, version control, and CI/CD workflows. Strong understanding of model performance evaluation, hyperparameter tuning, and maintenance using tools like Vertex AI Pipelines. More ❯

advice and best practices to overcome these challenges and successfully deliver the expected business outcomes. Skills and experience required Experience in any related software/DevOps/DevSecOps/MLOps/AI roles within a regulated engineering environment. CI/CD deployment Software/AI development and deployment in complex programmes Strong Data and Application understanding with underpinning Infrastructure solution More ❯

/conferences Experience with Git-workflow within a production team Experience with Agile product development Experience of working in a start-up Best practices in data engineering Familiarity with MLOps Experience with building Restful services Experience presenting in front of project stakeholders Keen business development interest Start date : Immediate Contract Type : Permanent Oxford Dynamics is committed to creating an inclusive More ❯

Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: Competitive Salary & Bonus : £35,000 – £45,000 plus performance-based incentives Hybrid Working : A flexible mix of office and remote work Career More ❯

to complex business problems, with the goal of improving supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation. You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery . Key Responsibilities Lead and mentor a data science team focused … mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems. Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions. Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines. Champion the integration of model outputs into wider data and reporting platforms. Clearly communicate technical insights and model outcomes … functional squads. What You’ll Get in Return A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance. Dedicated support from MLOps and Engineering teams to accelerate delivery. Access to career development support including coaching, mentoring, and leadership training . A competitive salary package including car allowance , bonus , and comprehensive benefits such More ❯

Have hands-on experience with LLMs , ML/DL frameworks like PyTorch, TensorFlow, LangChain ✅ Know how to deploy, monitor & optimise ML models in real-world systems ✅ Are comfortable with MLOps tooling (CI/CD, Docker, Kubernetes) & cloud platforms (GCP/AWS/Azure) ✅ Want to build first-of-its-kind AI infrastructure with a lean, focused, high-performing team ✅ Love … building smart, scalable tech that makes a massive impact What you’ll do: Build production-grade AI/ML systems (NLP, OCR, LLM-based) Develop and manage robust MLOps pipelines and infrastructure Optimise models for performance, scalability, and cost Deploy observability tools (OpenTelemetry, Grafana) Collaborate with software engineers to embed AI into the product using APIs Create real-time, context More ❯

/conferences Experience with Git-workflow within a production team Experience with Agile product development Experience of working in a start-up Best practices in data engineering Familiarity with MLOps Experience with building Restful services Experience presenting in front of project stakeholders Keen business development interest If this looks of interest then please send your CV now and call for More ❯

business-critical machine learning models using Azure ML in production environments. Strong skills in data wrangling using Python, SQL, and ADF . Proficiency in CI/CD, DevOps/MLOps , and version control systems. Familiarity with data visualization and reporting tools, ideally PowerBI. Excellent communication and interpersonal skills, with the ability to convey technical concepts to non-technical stakeholders. Desirable More ❯

like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices and tools, such as MLflow or Kubeflow. Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems. A collaborative mindset and ability to work More ❯

managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting tools, ideally PowerBI. Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders. Experience More ❯

cutting-edge machine learning solutions that influence decision-making across a large, fast-moving business. You'll have access to vast datasets, modern tooling, and the support of experienced MLOps and Data Engineering teams – freeing you to focus on model innovation , business impact , and team leadership . Key Responsibilities Lead and coach a team of data scientists focused on pricing … senior stakeholders to prioritise and deliver key initiatives. Work cross-functionally with Marketing and Operations data teams to extend the reach of data science across the organisation. Collaborate with MLOps and Engineering teams to ensure seamless product delivery and integration. Promote the use and value of pricing models to non-technical stakeholders through clear and effective communication. Continuously improve the … flexible hybrid work model (Reading or London) and a collaborative environment. A role where your models directly shape pricing, influence profitability, and deliver real commercial outcomes. Support from seasoned MLOps and engineering teams – letting you focus on research, modelling, and innovation . If you’re passionate about pricing science and ready to step into a leadership role where your work More ❯

to-service communication, API gateways , and data management . AI & Machine Learning Platform: AI is a critical component of the product. You will lead the product vision for our MLOps pipelines and the integration of both traditional and generative AI models into our platform. DevOps & Automation: You will be responsible for the product strategy that underpins engineering enablement. This includes … AWS , and system architecture design. Deep understanding of microservices , Docker , security best practices, DevOps principles, CI/CD , and system monitoring. Direct experience with AI/ML products, including MLOps and the productization of machine learning models (both traditional and generative). Proven ability to bridge business and technical perspectives to make informed trade-offs between speed, quality, and scalability. More ❯

core AI platform capabilities, supporting a Machine Learning Engineer on classical ML projects, and building the foundation for a future Data Science function. You will also define LLMOps and MLOps practices and ensure the infrastructure is in place to support long-term AI success across the business. Key Responsibilities: Strategy & Leadership Collaborate over the AI roadmap across GenAI, ML, and … lifecycle automation. Maintain awareness of emerging models and integration strategies. Machine Learning Engineering: Support the ML Engineer in model development, deployment, and monitoring. Contribute to pipelines, experimentation design, and MLOps enablement. Provide code and architectural reviews, as well as technical mentoring. Data Science Enablement Act as Data Scientist to support analytics and decision-making needs. Develop experimentation frameworks, metric definitions … and deploying GenAI applications in production. Strong hands-on knowledge of LLMs, prompt engineering, and retrieval-augmented generation (RAG). Practical experience with traditional ML, including data pipelines and MLOps workflows. Working knowledge of statistical modelling and experimentation. Proficiency in Python and at least one additional general-purpose language. Strong understanding of cloud-native architectures (AWS preferred). Experience leading More ❯

shipping and maintaining ML models in production, including performance monitoring and optimization. Strong Programming: Proficiency in Python and ML libraries (e.g., PyTorch, scikit-learn, Hugging Face, etc.); familiarity with MLOps tooling and cloud environments (AWS/GCP/Azure). Analytical & Communication Skills: Ability to clearly explain complex ideas, trade-offs, and results to diverse audiences. Nice to Have: Experience More ❯

investigate failure cases or drift, and recommend iterative improvements Track and report key performance and operational metrics Contribute to best practices in version control, testing, CI/CD, and MLOps Share expertise through peer code reviews, documentation, and collaborative learning initiatives Stay current with emerging trends in AI/ML, particularly in areas such as LLMs, NLP, and intelligent document More ❯

Experience of deployment in a cloud environment Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas Experience with API development SQL experience Software engineering experience DevOps/MLOps experience Good working understanding of CI/CD If you hold the experience and technical skills outlined above which would enable you to hit the ground running, please apply to More ❯

Who are we? Look at the latest headlines and you will see something Ki insures. Think space shuttles, world tours, wind farms, and even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. More ❯

Founding Machine Learning Engineer - AI Start-Up (On-Site | Equity + Salary) A rare opportunity to join one of London’s most exciting AI start-ups at the ground level! Backed by top-tier investors and led by a world More ❯