20 of 20 Permanent MLOps Jobs in the South West

PyTorch, or Java-based ML libraries) Strong problem-solving and communication skills Preferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with MLOps practices and model lifecycle management Knowledge of event-driven architectures (Kafka or similar) Experience with DevOps tooling and infrastructure as code Exposure to Generative ...

Intelligence, Data Science, or a related technology discipline Minimum 2:1 degree classification (or equivalent) Desirable Azure OpenAI, AWS Bedrock and Google Gemini experience MLOps, Data Engineering or Platform Engineering experience Experience leading technical teams Knowledge of Agentic AI, AI Agents and emerging AI frameworks What's On Offer? Opportunity ...

Learning Applied machine learning, computer vision, object detection, image classification, model development and evaluation, data annotation and curation, training pipelines, performance optimisation, edge ML, MLOps, deployment and maintenance of ML solutions, Python development, Python-based ML frameworks, PyTorch, TensorFlow, sklearn, OpenCV, NumPy, feature development, code review, pytest, linting, bug fixing ...

Computer Science, Data Science, Machine Learning, or related field. Proven experience building and deploying AI applications in large-scale production environments. Experience with MLOps practices and tools for managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding ...

knowledge in the following: Python AWS Kubernetes Spark & distributed computing dbt Terraform Data Warehousing (we use Databricks but experience with other platforms is fine) MLOps implementation (desirable but not required) Airflow (or other orchestration tooling) Governance Why else you'll love it here Wondering what the salary for this role ...

PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces around them Experience with DevOps and MLOps Degree-level qualification in computer science or related field Deep understanding of Python Familiarity with Linux, bash, and the command line Ability to write logical ...

development and deployment of ML and AI models to prove and deliver tangible commercial value. Act as a technical bridge between Data Science and MLOps to embed best practice deployment techniques across the team. Take hands-on ownership of big projects, working with a large, event-based data set. Research ...

obligations. Design scalable, secure, and resilient data platforms, including cloud, hybrid, and on‐premise architectures. Lead architecture for advanced analytics, machine learning, GenAI, and MLOps, ensuring production‐grade robustness. Establish AI governance, data management, and responsible AI frameworks, including security, privacy, explainability, and model risk controls. Translate business outcomes into ...

Event Hubs, or Kinesis for real-time data processing Knowledge of data architectures supporting AI/ML workloads, including vector databases, feature stores and MLOps pipelines Experience processing and managing unstructured data types (text, images, logs, sensor data) Understanding of Lambda and Kappa architectural patterns and when to apply each ...

Knowledge of C++, Python, PyTorch, OpenCV, CUDA, TensorRT, Git, WSL, Docker, Jira/Confluence Machine Learning and Deep Learning Computer Vision methodologies and algorithms MLOps Developing AI for use on Edge Computers Research and prototyping Benefits: Annual Company Bonus – Based on company performance 25 Days holiday not including bank holidays ...

multi cloud with strong AWS depth). Deep understanding of AI/ML solution patterns (data pipelines, training, inference, monitoring, and MLOps) and how they map onto AWS services (e.g. SageMaker, Batch, Step Functions, EKS/ECS, data lake components). Proven ability to take research and prototype environments ...

About AXA: AXA is a global leader in insurance and financial services, dedicated to helping customers protect what matters most to them. As the sixth-largest insurance company in the world, we provide a wide ...

designing and building APIs, distributed systems, and event-driven architectures in modern programming languages such as Python, TypeScript, Java, Go, or similar Familiarity with MLOps practices, model monitoring, observability, versioning, and automated deployment pipelines preferred Strong problem-solving skills with the ability to navigate ambiguity, experiment rapidly, and deliver impactful … cost efficiency while supporting increasing AI adoption and usage Implement engineering best practices around observability, monitoring, testing, security, and operational excellence Establish and champion MLOps practices including model lifecycle management, prompt versioning, automated evaluation, and continuous improvement Build reusable frameworks, developer tooling, and platform capabilities that accelerate AI innovation across ...

Purview, Azure ML, Databricks, MLflow or Microsoft Fabric . Knowledge of DAMA-DMBOK, NIST AI RMF, ISO 23894, ISO 27001 or UK GDPR . MLOps, model monitoring or AI risk/control experience. Benefits: Salary up to £80,000 25 days holiday + bank holidays Private Medical Insurance Hybrid working ...

leaders. You are aligned and accountable. You are comfortable with ambiguity, fast cadence, and ownership. Excuses do not ship parts. Execution does. You have MLOps and production deployment experience at scale. Great plus: Background in composites, advanced manufacturing, aerospace, automotive, or defense. Experience with computer vision applied to automated inspection ...

Strong working knowledge of ISO 27001 (Information Security Management) and ISO 42001 (Artificial Intelligence Management System). Hands-on understanding of data management principles, MLOps lifecycles, and model auditing. Must have active UK SC clearance (or active DV clearance). #J-18808-Ljbffr ...

lifecycle - assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and DevOps & MLOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems. THE WORK Formulate real-world problems into practical, efficient, and scalable … Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including ...

This job is with WTW, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Is this the next step in ...

data solutions. This role will see you building and maintaining scalable platform capabilities, troubleshooting existing services, and providing technical support to Data Scientists and MLOps teams working across a range of technologies. Key Responsibilities of the Analytics Platform Engineer Design, build and maintain scalable analytics platforms and cloud-based infrastructure. … platform capabilities while enhancing and maintaining existing analytics solutions. Troubleshoot technical issues, implement improvements and optimise platform performance. Collaborate closely with Data Scientists, MLOps Engineers and other technical teams to deliver reliable, secure and high-performing solutions. Adapt to a varied workload, solving complex engineering challenges across a range ...

will develop, test, deploy, and enhance platform capabilities, resolve issues within existing analytics services, and provide hands-on engineering support to Data Scientists and MLOps teams working across a range of technologies. You will operate in a dynamic environment with varied and sometimes unfamiliar technical challenges, requiring strong problem-solving … lifecycle. Design, develop, test, and deployment of a new analytic hosting platform. Bugfixes and feature requests for existing mission facing analytics. Engineering support to MLOps engineers and Data Scientists. These are unpredictable and highly variable requirements, potentially using unfamiliar technology, so a flexible style is required. In this role ...