16 of 16 MLOps Jobs in Reading

pipelines. Familiarity with data lake architectures and tools like Delta Lake , LakeFS , or Databricks . Knowledge of security and compliance best practices (e.g., SOC2, ISO 27001). Exposure to MLOps platforms or frameworks (e.g., MLflow, Kubeflow, Vertex AI). What We Offer Competitive salary + equity Flexible work environment and remote-friendly culture Opportunities to work on cutting-edge AI More ❯

to embed intelligent features into our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align with broader business goals. Support More ❯

and frameworks to enhance the overall security posture of AI/ML and other business systems. Develop and maintain relationships between data scientists, data engineers, developers, operations (DevOps, DataOps, MLOps) and business unit leaders to govern and support scalability of the ML and AI initiatives. Essential skills/knowledge/experience: Solid experience as a Security Architect, with a focus More ❯

SVM, tree-based methods, and NLP. Expertise in generative AI tools: Experience with prompt-engineering, fine-tuning language models, and selecting the right models for various tasks. Proficiency in MLOps: Knowledge of building production applications in cloud architecture (Azure, AWS, or similar), and understanding of best practices for the full software development life cycle. Strong programming skills: Proficient in Python More ❯

SVM, tree-based methods, and NLP. Expertise in generative AI tools: Experience with prompt-engineering, fine-tuning language models, and selecting the right models for various tasks. Proficiency in MLOps: Knowledge of building production applications in cloud architecture (Azure, AWS, or similar), and understanding of best practices for the full software development life cycle. Strong programming skills: Proficient in Python More ❯

Trainer/Instructor/Lecturer/Teacher Consultant/Coach/Mentor/Educator ) Ability to explain complex topics clearly and adapt to different learning levels. Familiarity with modern MLOps practices, reproducibility, and collaborative workflows. Practical experience deploying or training models in cloud environments (AWS, GCP or Azure) This is a fully remote working position & salary is £65,000, with 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 ❯

for data science (DS). Low/no code approach to DS/AI IDEs & notebooks. Git & GitHub (or similar) Production: Serving to APIs, e.g. Streamlit, Dash Production particularly MLOps/LLMOps Good To Have Skills Fabric Copilot, Copilot Studio PySpark, R, Julia Databricks CRM familiarity, e.g. Salesforce Able to learn new skills on the fly, staying topical in a 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 ❯

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 ❯

Press space or enter keys to toggle section visibility Location London, Reading Job Family Digital & Technology Job Type Full Time Posted Date 06-May-2025 Ref # 66720 We have an amazing opportunity for a Senior Data Scientist to join More ❯

Location: Reading (RG1 1LZ) (2 days p/w in office) Salary: £75k-£85k + bonus Industry: Finance Tech Stack: Python, SQL, Tableau, AWS, Azure 👩🏻‍💻 Great opportunity for a talented Engineer (Python, SQL, Tableau, AWS, Azure) to join a retail More ❯

data. Collaborate with legal SMEs to translate domain knowledge into scalable machine learning solutions. Continuously evaluate model performance, ensuring accuracy, fairness, and compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or More ❯

ML systems, data pipelines, and CI/CD processes. Conduct security risk assessments and threat modelling on AI/ML workflows. Drive secure coding practices and integrate security into MLOps/DevOps pipelines. Address challenges such as adversarial attacks, data poisoning, and prompt injection. Define access control, authentication, and encryption standards across platforms. Work with data scientists and engineers to More ❯

Data/MLOps Engineer Hybrid Working - 2 days p/w in office (Reading, RG1 1LZ) Pays £75k-£85k Data/MLOps Engineer - Python, SQL, AWS, Azure Oliver Bernard have partnered with a retail bank undergoing a data transformation. You'll be joining their core Data team and be responsible for deploying tooling through cloud platforms, utilising new LLM models … and building out new pipelines. Data/MLOps Engineer - Python, SQL, AWS, Azure Key Skills and Experience: Python SQL Tableau, PowerBI Terraform AWS, Azure This role is hybrid working from their offices in Reading, RG1 1LZ (3 days p/w). VISA sponsorship is not available for this role. Budget is £75k-£85k + benefits including bonus. 2 stage … interview process - 1st stage call with manager, final stage with team. Data/MLOps Engineer - Python, SQL, AWS, Azure More ❯

AI features, including retrieval-augmented generation (RAG), internal LLM-based tools, and content delivery workflows. Experience with vector stores, agent frameworks, or scalable data workflows is all relevant here. MLOps & Deployment: Build and maintain the infrastructure behind our AI stack – including serving models via APIs, monitoring performance, and deploying systems to the cloud. AWS is a plus, but experience with More ❯