401 to 425 of 601 MLOps Jobs in England

data pipelines across batch and streaming components, while shaping the platform with CI/CD, tooling and governance. You will collaborate with Data Science, MLOps, Product and commercial teams to deliver reliable data solutions and mentor others, ensuring clear communication with stakeholders. #J-18808-Ljbffr ...

seeks a Machine Learning Engineering Lead to design, deploy, and govern production AI services for legal content products. You will lead architecture direction, MLOps practices, and responsible AI controls while guiding a team of engineers. You’ll work with LLM/RAG capabilities, embeddings, and multi‐step agentic workflows, ensuring ...

vision and delivering practical solutions at scale on our payments platform. You will collaborate across teams to research and validate AI use cases, design MLOps components, and drive production-ready AI with governance and security considerations in a fast-paced fintech environment. The hybrid model supports collaboration and growth. #J ...

seeking a Senior Platform Engineer to build and operate an Azure-based data and AI platform. This hands-on role involves Terraform, network design, MLOps pipelines, and DevSecOps patterns for daily engineering use. You will design landing zones, manage security with proper IAM, monitor with Azure Monitor, and enable cost ...

build reusable accelerators that scale beyond engagements. This role focuses on production-ready agentic architectures, LLM orchestration standards, RAG pipelines, and end-to-end MLOps governance across multiple platforms and providers. #J-18808-Ljbffr ...

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 ...

using tools and frameworks such as LLaMAFactory, Hugging Face Transformers, LangChain, or OpenLLM for model deployment, serving, or pipeline development. Comfortable with using modern MLOps practices for NLP workflows. Demonstrated ability to publish research results in top-tier NLP conferences (e.g., ACL, EMNLP, NAACL, NeurIPS, ICLR) or practical contributions ...

create real commercial leverage Skills and Experience Proven leadership in defining and delivering enterprise AI strategy, including GenAI Strong understanding of AI platforms, MLOps, and modern AI tooling (without needing to be hands‐on) Experience translating AI opportunities into commercially impactful use cases at scale Exceptional communication, influence, and stakeholder ...

efficiency and training stability. Data strategy & feature engineering: design representation, augmentation, and synthesis strategies for complex, constrained biological datasets. Collaborative hand-off: partner with MLOps so prototypes are built for stability and transition cleanly into scaled production. What we're looking for Advanced ML & deep learning: deep theoretical and practical ...

experiments, ideally at scale Experience post-training large language models Strong software engineering practice: advanced git workflows, testing, containerisation, code review, etc Familiarity with MLOps tools and training across multi-GPU clusters An understanding of specification-aware programming (Verus, Dafny, TLA+), proof assistants and verification tools ( LEAN, Isabelle) AI-natives ...

software as a medical device Time-series or signal processing workloads, physiological data, or scientific instrumentation Experiment tracking, model registries or MLOps tooling, aimed at research reproducibility rather than production inference Behaviour-driven testing or specification-by-example as an interface between research and engineering Introducing agent-assisted workflows into ...

financial services, life sciences, or federal/government. Familiarity with modern AI data infrastructure ecosystems: GPU clusters, parallel file systems, object storage, and MLOps pipelines. Track record of scaling SE teams and operating models in high‐growth, rapidly evolving technology environments. Experience establishing SE Center of Excellence practices: demo environments ...

software code development Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps Designs and implements data engineering solutions, leveraging modern big data technologies Contributes to software engineering communities of practice and events that explore new and emerging technologies Embraces … experience developing Production-scale Cloud-native data engineering solutions in commercial environments Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds and Overall knowledge of the Software Development Life ...

quality and reliability Helping to standardise and reuse AI workflows, making it easier for teams across different domains to build consistently and efficiently Applying MLOps principles to AI systems, including CI/CD, monitoring, model management and feature governance Partnering with Cloud Infrastructure teams to design secure, cost-effective environments … prompting, retrieval augmented generation (RAG) and fine tuning LLMs Familiar with software development practices including version control, CI/CD, containerization, and monitoring for MLOps Experience in taking projects from inception to production. A collaborative mindset with strong communication skills and the ability to work effectively across multidisciplinary teams. Motivated ...

commercial value Design, develop, and deploy scalable machine learning, predictive analytics, and AI applications Drive technical best practices across data science, experimentation, model development, MLOps, and software engineering Collaborate closely with Data Engineering, Platform, and Product teams to deliver production‐grade solutions Contribute to the evolution of Howden … Skills Proven track record of building and deploying production‐grade AI/ML applications that generate measurable business value Experience working with Data Engineering, MLOps and Product teams to bringing Machine Learning systems from research all the way to deployment and maintenance Excellent Python programming skills and hands on experience ...

commercial value* Design, develop, and deploy scalable machine learning, predictive analytics, and AI applications* Drive technical best practices across data science, experimentation, model development, MLOps, and software engineering* Collaborate closely with Data Engineering, Platform, and Product teams to deliver production-grade solutions* Contribute to the evolution of Howden … Skills*** Proven track record of building and deploying production-grade AI/ML applications that generate measurable business value* Experience working with Data Engineering, MLOps and Product teams to bringing Machine Learning systems from research all the way to deployment and maintenance* Excellent Python programming skills and hands on experience ...

Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state ...

Senior ML Ops Engineer London (Hybrid, 1-2 days per week) | £75,000 - £85,000 + 10% Bonus This is an opportunity to join a growing AI and data organisation that is using advanced analytics ...

Face Transformers, timm, scikit‐learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration‐driven training runs. Containerisation and infrastructure as code: Docker and CUDA‐based ...

Face Transformers, timm, scikit-learn, NumPy, pandas, OpenCV. Production experience on AWS, specifically Amazon SageMaker: training and processing jobs, pipelines, model registry, endpoints. Practical MLOps: experiment tracking and model versioning with MLflow, hyperparameter optimisation, and reproducible, configuration-driven training runs. Containerisation and infrastructure as code: Docker and CUDA-based ...

design, deploy and maintain production ML pipelines powering personalised rankings across search results and recommendations. You will collaborate with ML Scientists, Backend Engineers and MLOps to build scalable ranking models, improve latency, observability and real-time serving, and help harden the ML infrastructure for ranking systems. #J-18808-Ljbffr ...

production ML—owning problems end-to-end to accelerate model delivery. You’ll collaborate with the ML team to improve data quality, observability, and MLOps practices, while scaling infrastructure for faster iteration and reliability. #J-18808-Ljbffr ...

institutions, and enterprises with demanding GPU workloads. Role requires deep ML/infra knowledge, hands‐on Kubernetes, and the ability to discuss model training, MLOps, and hardware considerations with credibility. Up to 40% travel expected. #J-18808-Ljbffr ...

models with cloud services to deliver production-ready outcomes. The role spans the full lifecycle, from problem framing and data assessment to model selection, MLOps pipelines, validation, and collaboration with clients and cross-functional teams to drive measurable business value. #J-18808-Ljbffr ...

built, governed, and evaluated across the Global Public Sector team. You will define standards for responsible AI, model governance, and production MLOps used by multiple engineers and clients. You will architect high-risk AI systems, lead incident resolution related to model safety and data integrity, and coach senior engineers while ...