226 to 250 of 306 MLOps Jobs in England

across fintech use cases. Architect the integration layer for how ~1,500 commercial team members interact with AI—including model governance, tooling, infrastructure, and MLOps frameworks. Lead and grow a high‐calibre team of Data Scientists, fostering a culture of rapid experimentation, technical excellence, and continuous learning. Drive innovation … Generative AI, Agentic AI, deep learning, and large‐scale ML deployment—staying ahead of the curve on foundational models, LLMs, and autonomous agents. Champion MLOps best practices, cloud‐native development (Azure preferred), and scalable production deployment pipelines. Collaborate cross‐functionally with Sales, Product, Engineering, and more to embed AI capabilities ...

models into complex enterprise workflows. Oversee the full technical lifecycle, from selecting the right model architecture to ensuring robust CI/CD and MLOps pipelines. Deploy and optimise models using cloud services like AWS Bedrock and Azure AI Foundry, or self-host them on GPU/CPU hardware using tools … Ollama. Implement frameworks and approaches to evaluate model performance against business objectives, both pre-deployment and on an ongoing basis as part of the MLOps lifecycle. Assess and optimise for performance, cost-efficiency, and reliability, ensuring AI outputs meet the rigorous standards required for our Security & Justice clients. Design ...

Experience fine‐tuning LLMs (e.g., LoRA, QLoRA, RLHF) specifically for domain‐specific enterprise applications. Taken responsibility of models from concept to production, utilising strong MLOps and LLMOps practices to ensure scalable, reliable, and monitorable deployments. High proficiency in Python and modern software development practices, including rigorous testing, code reviews … Computer Science, Artificial Intelligence, Statistics, Data Science, or a related quantitative field. Experience working with scalable cloud infrastructure (AWS, GCP, or Azure) and MLOps tools for model training, monitoring, and deployment. Background in forecasting, planning, or analytics applications. Familiarity with Anaplan or similar enterprise planning platforms. Experience with A/ ...

better systems that deliver real business value. Key Responsibilities Technical Leadership & Ownership (Individual Contributor) Act as the technical lead for Machine Learning Engineering and MLOps across London Market. Technically lead the most complex and business‐critical ML systems, from architectural design through to production operation. Define and evolve production … experience as a senior or principal Machine Learning Engineer delivering production ML systems at scale. Proven track record of owning or shaping ML platforms, MLOps frameworks, or critical ML infrastructure. Experience operating in complex, cross‐functional environments (insurance or financial services experience is advantageous but not essential). Technical Expertise ...

About Us Have you ever wanted to build something that doesn’t just improve the status quo, but makes it 100x better? Not just a small step forward, but a complete reinvention. That’s what ...

This is a fantastic opportunity to work as an MLOps Engineer on a remote basis, outside IR35, for a growing pharmaceutical company. The key skills required for this MLOps Engineer position are: MLOps AI AWS Python Terraform Kubernetes DevOps background If you do have the relevant experience for this long … term remote contract MLOps Engineer role, outside IR35, please do apply. ...

optimizing the ML systems that power drug discovery processes, ensuring scalability across vast datasets. The ideal candidate will have hands-on experience in infrastructure, MLOps, and distributed systems, and be excited to work with ML technologies. The position is hybrid, requiring office presence at least 50% of the time. Compensation ...

FHIR . Proven ability to engage with senior executives and carry significant sales targets. Preferred Skills Experience with multi-agent AI frameworks and MLOps for AI systems. Background in patient engagement tools or digital health solutions . Expertise in clinical trials , pharmacovigilance , or patient support services . Why Join ...

MLOps Engineer, Palantir Platform Fully Remote 6 Month Contract Outside IR35 £550 to £650 per day The Company They are a large, data driven organisation operating at scale, with a strong focus on using advanced analytics and machine learning to inform decision making. The business invests heavily in its data … platforms and engineering capability, creating an environment where robust MLOps practices are essential. Teams are collaborative, delivery focused and used to working with senior technical stakeholders. The Role and Deliverables Design, build and maintain MLOps pipelines on the Palantir Foundry platform. Enable reliable deployment, monitoring and retraining of machine learning ...

helping to build out the wider ML function. You'll operate as a hands-on technical leader, setting best practice across ML pipelines, MLOps, and data products while working closely with Data Scientists, Engineers, and senior stakeholders. Key responsibilities include: Leading and championing ML Engineering as a core capability across … organisation Designing, building, and productionising end-to-end ML pipelines aligned to business strategy Implementing robust MLOps processes (CI/CD, model deployment, monitoring, governance) Delivering ML solutions for complex NLP and LLM use cases, including large-scale document processing Collaborating closely with Data Scientists to support model development, fine ...

signal processing to deliver real-time audio quality improvements at scale — deployed across cloud, edge and embedded environments. The role A high-impact MLOps role owning end-to-end ML pipelines — from data through training, evaluation and deployment. You’ll work closely with audio ML researchers and DSP engineers … small ML team. What they’re looking for Proven experience building and operating production ML systems Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps, CI/CD and model lifecycle management Cloud platforms (AWS, GCP or Azure) and containers/Kubernetes Experience with low-latency or real-time systems; familiarity ...

MLOps Platform Manager (Palantir) London Rate: £550-£650 Outside IR35 Per Day Work Type: Fully remote Start: ASAP The Company They are a well established organisation with a strong enterprise data estate and a clear commitment to using data and AI responsibly at scale. The business operates in a complex … central platform function focused on operational excellence. The Role and Deliverables Own the day to day operation of Palantir platforms and associated MLOps services, ensuring availability, performance and a strong user experience. Establish and run service management processes including incident, problem and change management, supported by clear documentation and runbooks. ...

technologies where appropriate • Validate data, perform testing and ensure analytical output quality • Monitor model performance and support ongoing optimisation and governance • Contribute to MLOps practices including deployment, versioning and monitoring • Translate technical findings into clear business recommendations • Develop reusable analytical assets, datasets and reporting solutions • Collaborate with stakeholders to identify … similar quantitative discipline Desirable • Experience with Microsoft Fabric or modern cloud-based data platforms • Exposure to NLP, LLMs or Generative AI technologies • Experience with MLOps practices and CI/CD pipelines • Understanding of data governance and model governance frameworks • Previous experience within financial services, fintech or regulated environments • Leadership ...

dependencies to support executive decision‐making. Provide technical guidance across the AI landscape including generative AI, agentic systems, retrieval‐augmented generation, fine‐tuning, MLOps, and on‐premise/cloud‐native ML platforms, ensuring recommendations are grounded in implementation reality. Collaborate with the client’s internal teams (programme management, data engineering … complex, regulated, or high‐security environments. Deep technical fluency across modern AI/ML stacks: on‐premise and cloud platforms (AWS, Azure, GCP), MLOps tooling, LLM orchestration frameworks, data engineering pipelines, and AI governance. Exceptional ability to translate technical complexity into strategic narratives for non‐technical senior stakeholders. Strong commercial ...

understanding of the full ML lifecycle and strong software/platform instincts - you know what it takes to run reliable ML at scale – including MLOps tooling and practices Experience raising operational standards: SLIs/SLOs, monitoring, incident management, and production reliability Budget ownership, including infrastructure cost management and vendor oversight … associated ML/DS libraries (scikit-learn, NumPy, LightGBM, Pandas, LangChain/LangGraph, TensorFlow, etc.) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc MLOps/DevOps: Terraform, Docker, Airflow, MLFlow Monitoring and evaluation platforms including New Relic and Braintrust More information Enjoy fantastic perks like private healthcare & dental insurance ...

As a Lead Engineer, you will be part of our Enterprise AI engineering team to deliver secure, reliable, and innovative AI solutions across our business. In this role, you’ll be responsible for advancing our ...

play a pivotal role in transforming and modernising our machine learning platform. You’ll collaborate across the organisation to define and implement MLOps best practices, while taking charge of designing, implementing, and maintaining the infrastructure, essential for the development and deployment of machine learning models. Working closely with Data Scientists … learning models into our production systems, driving innovation and excellence within AXA UK. Key responsibilities: Contribute to the design and the development of robust MLOps, and Agentic Ops frameworks that will enhance our capabilities and drive value across AXA. Take offline models data scientists build and turn them into ...

play a pivotal role in transforming and modernising our machine learning platform. You’ll collaborate across the organisation to define and implement MLOps best practices, while taking charge of designing, implementing, and maintaining the infrastructure, essential for the development and deployment of machine learning models. Working closely with Data Scientists … learning models into our production systems, driving innovation and excellence within AXA UK. Key responsibilities: Contribute to the design and the development of robust MLOps, and Agentic Ops frameworks that will enhance our capabilities and drive value across AXA. Take offline models data scientists build and turn them into ...

play a pivotal role in transforming and modernising our machine learning platform. You’ll collaborate across the organisation to define and implement MLOps best practices, while taking charge of designing, implementing, and maintaining the infrastructure, essential for the development and deployment of machine learning models. Working closely with Data Scientists … learning models into our production systems, driving innovation and excellence within AXA UK. Key responsibilities: Contribute to the design and the development of robust MLOps, and Agentic Ops frameworks that will enhance our capabilities and drive value across AXA. Take offline models data scientists build and turn them into ...

into advanced techniques, including LLMs, RAG architectures, and Generative AI applications to create new forms of automated analysis and augmented intelligence products. Production Engineering & MLOps : Translate validated prototypes into robust, production‐ready specifications, and lead the implementation of MLOps best practices (CI/CD, monitoring, serving) required for the reliable …/DL models. Experience with advanced analysis of unstructured or multi‐modal data (e.g., high‐dimensional feature vectors, dense embeddings) is highly valued. MLOps Mindset : Proven track record of transforming R&D proofs‐of‐concept into robust, scalable, and monitored production‐grade ML solutions. Engineering Rigor : A background in software ...

Role Summary We are seeking a Principal Machine Learning Engineer (SageMaker, MLOps, Model Governance & Explainability) to provide technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that … architecture for the matching platform, including data pipelines, model training workflows, inference runtimes, and telemetry ecosystems. Lead adoption of best‐in‐class MLOps patterns, platform tooling, and AWS SageMaker capabilities across training, processing, registry, monitoring, and deployment. Partner with platform, security, and data engineering teams to implement scalable data lakehouse ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...

strategy. Designing, building, and productionising ML pipelines aligned to business goals. Delivering NLP and LLM-driven solutions, including fine-tuning and deployment. Implementing strong MLOps practices across model training, deployment, and monitoring. Working closely with Data Scientists to support, maintain, and improve models in production. Building APIs and data products … pipelines. Hands-on experience with Databricks and Azure. Practical experience with NLP and LLMs, including fine-tuning and applied use cases. Solid understanding of MLOps, CI/CD for ML, and production model monitoring. Exeperience with stakeholders and translating business problems into technical solutions. Experience building or integrating APIs, such ...