1 to 25 of 32 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 ...

Data Engineering - Python, SQL, ETL/ELT, modern cloud data platforms, Spark/Databricks and data architecture AI & Machine Learning - ML Engineering, MLOps, Python, model deployment, evaluation, LLM/GenAI and production AI Technical Leadership - Senior/Lead engineering roles across Cloud, Platform, Data and AI The organisations vary ...

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 ...

other product and engineering teams to deploy AI safely, rapidly, and at scale. You will democratize AI across the organization, establish modern LLMOps/MLOps practices, and directly impact the Actian Data Intelligence Platform by introducing agentic workflows, intelligent data pipelines, and cutting-edge capabilities. Core Responsibilities: Internal AI tooling ...

other product and engineering teams to deploy AI safely, rapidly, and at scale. You will democratize AI across the organization, establish modern LLMOps/MLOps practices, and directly impact the Actian Data Intelligence Platform by introducing agentic workflows, intelligent data pipelines, and cutting-edge capabilities. Core Responsibilities: Internal AI tooling ...

internal stakeholders.** *Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices.** *Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment.** *Experience of appropriate version control and environment management (such as venvs or Docker).** *Experience of writing technical project ...

internal stakeholders. Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices. Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment. Experience of appropriate version control and environment management (such as venvs or Docker). Experience of writing technical project ...

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 ...

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 Learningand Gen AI models for various use cases based on the business needs, data availability,systemand infrastructure requirements - including edge device ...

performance and cost-effectiveness. AI: Develop and deploy AI/ML models into production environments. Build scalable inference pipelines and AI APIs. Implement MLOps workflows for model versioning, monitoring, and retraining. Collaborate with data scientists to productionize machine learning solutions. Evaluate and optimize AI model performance and operational efficiency. Database ...

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 ...

skills Experience with Linux operating systems (e.g. Red Hat, Ubuntu) Experience working within a variety of development frameworks and practices e.g. DevOps, DevSecOps, SCRUM, MLOps, XP. Experience with data analysis and manipulation tools (e.g. Pandas) Experience of a broad section of the Software Development Lifecycle (SDLC) with specific focus ...

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 ...

C#/.NET services. Performance & Scalability : Optimize GPU/CPU utilization, batching strategies, and memory management. Plan for multi-model and multi-tenant scenarios. MLOps & Lifecycle Management : Implement model versioning, artifact registries, and deployment workflows. Set up monitoring, logging, and alerting for solver performance. Security & Compliance : Apply best practices ...

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 ...

Experience using Python and R to develop and deploy models in cloud environments (Azure experience is advantageous). Understanding of machine learning lifecycles and MLOps principles. Experience working with databases, APIs and collaborative development tools. Sharp problem-solving and analytical skills, with attention to detail and sound judgement. Confident communication ...

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 ...

commercial deployment, focusing on performance, reliability, and maintainability. Key qualifications include expertise in TensorFlow and Python, experience in API development, and familiarity with MLOps practices. Joining means working on cutting-edge ML solutions and collaborating with experts across various fields. #J-18808-Ljbffr ...

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 ...

appropriate performance metrics. Experience creating, managing, and interrogating graph databases (e.g., Neo4j). Experience with maritime, aerial, or other remote-sensing imagery. Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.) Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ ...

integration between connected devices, cloud services, data platforms, and engineering teams. As the capability matures, the role will provide a clear development path into MLOps and ML platform engineering, supporting model deployment, model lifecycle controls, ML pipeline automation, and governed promotion of machine learning solutions from development into production. … validation, monitoring, transformation and handover between operational platforms and analytical environments. Proactively identify opportunities to simplify, automate and strengthen digital platform delivery. Growth into MLOps and ML platform engineering Develop capability in MLOps practices such as experiment tracking, model packaging, model registry, model promotion and governed deployment workflows. Support ...

design, build, and evolve scalable analytics platforms, supporting the full lifecycle from development to deployment and optimization. Work in collaboration with Data Scientists and MLOps to tackle complex challenges across a modern stack, including cloud migration, and data management, in a hybrid UK setting with #J-18808-Ljbffr ...

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 ...