276 to 300 of 306 MLOps Jobs in England

making the function known Team Building Scale the team in line with what the roadmap demands – hiring across ML engineering, data science, and MLOps Develop the existing team, create career paths, and set technical and cultural standards What the First Year Looks Like 3 months: DS roadmap defined cross‐functionally … external presence. 12 months: DS is a recognised, embedded function with a track record of delivery. Experimentation is a working discipline used beyond DS. MLOps maturity has stepped up. The team has grown in line with what was needed to get here. What You Bring Must‐Haves 4‐5 years ...

through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating … through APIs Working with unstructured data to extract insights and build robust data pipelines Evaluating, tracking, and improving the performance of NLP models through MLOps Driving innovation through research, experimentation, and rapid prototyping of MVPs and POCs, collaborating with engineers and product teams to validate findings and plan execution Communicating ...

efforts, working with our technical teams to design, build and operate mission-critical machine learning capabilities. This includes everything from infrastructure and MLOps through to training, fine-tuning, deployment, and live model management. While you’ll be hands-on in engineering, your work will also be advisory, ensuring models … embedded models as needs evolve. Hands-on experience working alongside scientists and within deployment environments is central to this role, as is familiarity with MLOps tooling, scheduling, and orchestration. You’ll be comfortable working in cloud environments and with ML lifecycle tools such asWeights & Biases, and you’ll have Python ...

ML Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data ...

We’re excited to be partnering with a global engineering and technology business to support the growth of a brand-new data science team within their R&D function. This is a great opportunity to ...

We're working with a fast moving tech business looking for a Senior ML Engineer to own personalisation end to end. This isn't a research role. You'll be shipping models to production, building ...

Qureight’s mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI‐powered data and imaging curation platform enables the analysis of clinical imaging and ...

Qureight’s mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI‐powered data and imaging curation platform enables the analysis of clinical imaging and ...

PRINCIPAL DATA ENGINEER £80,000 + BENEFITS LEEDS (Hybrid) Looking for a role where you can truly influence how data engineering is done-while still getting stuck into the tech yourself? THE COMPANY: I'm ...

As the Presales AI Solutions Architect within our AI Practice, you'll play a key role in technological advancement, developing a team and leading successful projects in all UK sectors. You will have the opportunity ...

engineers to build and integrate ML models into tools produced for third-party developers. The ideal candidate has strong programming skills and experience with MLOps/LLMOps, and a relevant degree in Computer Science or a related field. This role offers opportunities for collaboration and innovation. #J-18808-Ljbffr ...

experimentation strategy, model optimisation and AI innovation Collaborating with Product, Engineering and Commercial teams to embed Data Science into core decision‐making Shaping scalable MLOps and ML infrastructure within AWS environments Mentoring and developing a technically strong team of Data Scientists and ML Engineers Influencing long‐term AI strategy … engineering Hands‐on experience with PyTorch and deploying scalable ML models Expertise in recommendation systems, pricing models or personalisation engines Strong understanding of MLOps, experimentation frameworks and ML infrastructure Experience operating within AWS cloud environments A commercially minded approach to AI, modelling and automation Track record of building, mentoring ...

quality into actionable product requirements. Lead products from concept to prototype to production, ensuring scalability, performance, and regulatory alignment. Establish agile, DataOps, and MLOps practices to accelerate deployment of analytics and AI solutions. Guide the integration of operational data across ecosystems (MES, LIMS, ERP, QMS, plant-level data, SCADA … pharma, biopharma, or large-scale manufacturing/supply chain. Strong technical fluency: data engineering & pipelines, cloud platforms, data science & AI/ML product delivery, MLOps/DataOps principles. Skilled at influencing product direction across cross‐functional, multi-region teams. A strategic thinker capable of shaping long-term transformation while executing ...

software. You'll come from either an Engineering or Data Science background, with a good understanding of the Data Science Toolkit (Programming, Machine Learning, MLOps etc) and bringing data science solutions into production. You therefore tick the majority of the following points: Key Requirements A higher degree in engineering, computer … building scalable and resilient systems. Commercial experience contributing to the success of high impact Data Science projects within complex organisations. Awareness of emerging MLOps practices and tooling would be an advantage e.g. feature stores and model lifecycle management. An analytical mind set and the ability to tackle specific business problems. ...

Protection and Legal, covering model risk, data privacy, transparency, human in the loop and auditing.* Build the target operating model for AI engineering and MLOps, including model lifecycle management, monitoring, incident response, versioning and cost/performance optimisation.* Set global standards for AI platforms, toolchains and integration patterns; ensure interoperability … grasp of responsible AI, security and compliance, including model risk management, privacy, data residency, human oversight and auditability.* Hands on understanding of AI/MLOps practices and platforms, including model lifecycle, observability, cost control, CI/CD, feature stores and data integration.* Experience defining and governing enterprise standards and architectures ...

Job Description We are seeking a Machine Learning Engineer with a strong foundation in Machine Learning/Deep Learning to join a cross‐functional team. You’ll work closely with data scientists and engineers to ...

involves creating scalable and secure infrastructures aligned with regulatory standards. The ideal candidate will possess strong leadership skills in cloud-native AI platforms and MLOps strategies, ensuring operational excellence in a highly regulated environment. #J-18808-Ljbffr ...

This hybrid role involves leading the design of ML platforms and infrastructure, ensuring effective deployment and monitoring of models. The ideal candidate has extensive MLOps experience, strong software engineering skills, and familiarity with cloud platforms such as GCP. Join a diverse team at iProov, working at the intersection of technology ...

Data Scientist (MLOps/GenAI Focus) Location: Bristol Salary: Competitive + Benefits Join a cutting-edge AI team working at the forefront of GenAI, MLOps, and secure cloud deployments within highly regulated environments. The Role Youll act as a technical specialist and team lead, delivering innovative machine learning solutions: Building ...

capabilities including LLM-powered and generative experiences Setting technical direction across modelling, evaluation and ML lifecycle management Partnering closely with Product, Engineering and MLOps teams Improving scalability, observability and speed-to-production across ML systems Leading and developing a high-performing team of ML specialists and leaders Acting … interest in LLMs, generative AI and AI-powered customer experiences Excellent stakeholder management and communication skills Strong cross-functional collaboration across Product, Engineering and MLOps Why This Role? Opportunity to define the future of ML & AI within a major consumer platform High visibility and influence across Product, Technology and Commercial ...

specific core subject areas, enable cross-functional collaboration with other departments at Apple, contribute to architecture discussions, code review and proposals. Responsibilities Driving MLOps/LLMOps excellence within the team: including evaluation pipelines, monitoring, observability, and deployment best practices Building and maintaining LLM evaluation pipelines to assess model quality, track … pair programming and architecture discussions with other members of the team Minimum Qualifications Strong programming skills (Python, Swift, Go or other language) Experience with MLOps/LLMOps toolkits and frameworks Comprehensive knowledge and hands-on experience with LLM evaluations A learning attitude to continuously improve self and team Preferred Qualifications ...

About the Company - Entrust Identity Verification: At Entrust, identity is no longer a compliance checkbox—it’s a real-time product problem shaped by machine learning, adversarial behavior, and high-stakes decisions. Every verification is ...

About the Team : You'll be joining the team leading Entrust's Identity portfolio, formerly known as Onfido (an AI- powered digital identity solution). Our technology helps businesses verify real identities using machine learning ...

proof of concept into scalable production systems Align machine learning initiatives with product, commercial, and operational goals Advise on architecture across LLMs, agentic systems, MLOps, data pipelines, and model deployment environments Support leadership teams with AI roadmap prioritisation, delivery oversight, and capability planning Improve collaboration between product, data, and engineering … 10+ years of experience across machine learning, AI, or data-driven environments Experience leading ML teams within production-scale businesses Strong understanding of LLMs, MLOps, AI platform architecture, and scalable ML systems Experience operating within high-growth SaaS, AI-native, TechBio, or data platform businesses Ability to connect technical ...

We’re searching for a Head of Analytics & Data Science to transform how analytics is produced and consumed across our business. You’ll have significant freedom to unite, shape and lead our combined team, working ...