1 to 25 of 85 MLOps Jobs in Central London

ML deployment, you will have the responsibility of managing projects with autonomy across the full data lifecycle. Responsibilities📝 As an ML Engineer at Un:hurd music, you'll be: MLOps and Model Deployment : Own the deployment, maintenance, and retraining of machine learning models in production environments, designing scalable system architectures to ensure performance and resilience. Data Collection and Integration : Develop More ❯

We are partnering with a prestigious investment bank to find a highly skilled and Hands-on Machine Learning Operations (MLOps) Lead. This role will be pivotal in building out a greenfield framework for the deployment and management of scalable AI/ML solutions, specifically for the front and Middle Office user base. The role is to define and set up … a greenfield standardized MLOps framework for capital markets and set up all the tools and best practices to educate data scientists and equip them with the right tools and expertise. You MUST be hands on. A strong understanding of Devops, Machine learning and Data engineering is required to enable to right candidate to implement the MLOps processes. This team are … areas and business stakeholders, so relationship building and good communication will be key. You will bring a expertise in data science or data engineering, with a specific focus on MLOps for at least 2 years . This platform is critical and will be rolled out across the bank, so we are looking for only the highest calibre candidates with experience More ❯

release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts for different audiences Proven track record More ❯

or GCP. ● Experience with Agile development methodologies. ● A strong understanding of ethical considerations in AI/ML. Preferred Qualifications: ○ Experience with deep learning and natural language processing. ○ Experience with MLOps and DevOps practices. ○ Experience with financial regulations and compliance requirements. ○ Degree in Computer Science, Data Science, or a related field. More ❯

machine learning lifecycle, designing sophisticated models, experimenting with cutting edge techniques and building robust, production-ready pipelines. You will also contribute to the technical architecture, champion best practices in MLOps, and guide the strategic direction of our AI capabilities. This is a hands-on role for someone who enjoys both deep technical work and cross-functional collaboration—driving forward innovation More ❯

global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI. 🌎 Location and Legalities This full-time MLOps Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa … sponsorship. 🚀 What You'll Do As an MLOps Engineer at Ultralytics, you will build and manage the infrastructure that powers our cutting-edge AI models, from training to deployment. You will be at the heart of our operations, ensuring our machine learning lifecycle is efficient, scalable, and robust. Key responsibilities include: Designing, building, and maintaining our MLOps infrastructure on cloud … that our state-of-the-art models are accessible, reliable, and performant for our global user base. 🛠️ Skills and Experience 5+ years of experience in a DevOps, SRE, or MLOps role. Strong proficiency in Python and extensive experience with ML frameworks like PyTorch. Proven experience building and managing CI/CD pipelines for machine learning systems. Deep expertise with containerization More ❯

/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI/ML concepts, including deep learning, neural networks, NLP, and machine learning algorithms. • Familiarity with MLOps principles and tools for deploying, managing, and monitoring ML models in production. • Excellent problem-solving skills, with a passion for building innovative and impactful AI solutions. • Google Professional Cloud Architect More ❯

Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary & Bonus : £35,000 – £45,000 plus performance-based incentives 🏡 Hybrid Working : A flexible mix of office and remote work 📈 Career More ❯

working with unstructured data and NLP-related datasets. Proficiency in one programming language, preferably Python with experience in data processing libraries such as Pandas, PySpark, or Dask. Familiarity with MLOps and deploying AI/ML models into production environments. Knowledge of Retrieval-Augmented Generation (RAG) frameworks or interest in learning and supporting RAG systems. Experience implementing scalable APIs and integrating More ❯

PREFERRED QUALIFICATIONS: Meteorological understanding/experience with weather modelling Prior knowledge or experience in the power markets or energy sector. Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps practices. Familiarity with data visualization tools (e.g., Tableau, Power BI). COMPENSATION & BENEFITS: Competitive salary + bonus. Comprehensive benefits package including health insurance, pension plan. Hybrid working arrangement (minimum More ❯

SENIOR MACHINE LEARNING ENGINEER - MLOPS REMOTE (Travel to London once per month) Up to £75,000 + £5,000 bonus + strong pension COMPANY: We are working with a leading telecoms/mobile network who are looking to change the game when it comes to the service it provides its customers. They are looking for an MLOps Engineer that is … passionate about tech and working within a fast paced environment. ROLE: Design, build, and deploy scalable machine learning models to solve complex business problems. Implement and maintain robust MLOps pipelines, ensuring efficient CI/CD processes for machine learning. Automate the deployment and monitoring of models in production to ensure continuous performance and stability. Collaborate closely with data scientists, helping More ❯

to complex business problems, with the goal of improving supply chain efficiency, optimise vehicle movement, and enhance operational workflows across the organisation. You’ll be supported by a modern MLOps and Data Engineering function, giving you the time and tools to focus on innovation , model development , and strategic delivery . Key Responsibilities Lead and mentor a data science team focused … mathematical optimisation techniques (e.g., Linear Programming , Scheduling , Graph Theory ) to complex business problems. Work cross-functionally with senior stakeholders to translate business requirements into scalable technical solutions. Collaborate with MLOps and Engineering teams to productionise models using robust and scalable pipelines. Champion the integration of model outputs into wider data and reporting platforms. Clearly communicate technical insights and model outcomes … functional squads. What You’ll Get in Return A leadership role where your work has direct and measurable impact on operational efficiency and bottom-line performance. Dedicated support from MLOps and Engineering teams to accelerate delivery. Access to career development support including coaching, mentoring, and leadership training . A competitive salary package including car allowance , bonus , and comprehensive benefits such More ❯

Have hands-on experience with LLMs , ML/DL frameworks like PyTorch, TensorFlow, LangChain ✅ Know how to deploy, monitor & optimise ML models in real-world systems ✅ Are comfortable with MLOps tooling (CI/CD, Docker, Kubernetes) & cloud platforms (GCP/AWS/Azure) ✅ Want to build first-of-its-kind AI infrastructure with a lean, focused, high-performing team ✅ Love … building smart, scalable tech that makes a massive impact 🧠 What you’ll do: Build production-grade AI/ML systems (NLP, OCR, LLM-based) Develop and manage robust MLOps pipelines and infrastructure Optimise models for performance, scalability, and cost Deploy observability tools (OpenTelemetry, Grafana) Collaborate with software engineers to embed AI into the product using APIs Create real-time, context More ❯

like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices and tools, such as MLflow or Kubeflow. Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems. A collaborative mindset and ability to work More ❯

AWS, Azure, or Google Cloud for AI model deployment. Data Visualisation: Ability to present insights effectively using tools like Matplotlib, Seaborn, Tableau, or Power BI. Model Deployment: Understanding of MLOps principles, APIs, and containerization (Docker, Kubernetes) for productionizing AI models. Business-Focused AI Application: Ability to translate AI solutions into measurable business impact. Why Wowcher is your Next Stop: Our More ❯

train very large AI models. Build and maintain efficient, scalable, and reliable AI infrastructure, tools, and pipelines to support the deployment of machine learning models in collaboration with the MLOps team. Continuously research and stay current with the latest advancements in AI, machine learning, and data science. Contribute to the growth of the AI team by sharing knowledge, providing mentorship More ❯

business-critical machine learning models using Azure ML in production environments. Strong skills in data wrangling using Python, SQL, and ADF . Proficiency in CI/CD, DevOps/MLOps , and version control systems. Familiarity with data visualization and reporting tools, ideally PowerBI. Excellent communication and interpersonal skills, with the ability to convey technical concepts to non-technical stakeholders. Desirable More ❯

leveraging cloud-native tools and services. AI Feature Integration Collaborate with engineering and product teams to embed AI-driven functionality into user-facing software. Technical Leadership Set standards for MLOps, automation, and performance tuning across the engineering team. Generative AI & LLMs Explore and integrate modern techniques such as large language models and generative architectures. Mentorship & Collaboration Support peers through code More ❯

managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting tools, ideally PowerBI. Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders. Experience More ❯

and pre-sales activities Maintain high billable utilisation while delivering exceptional client value Contribute to Made Tech's thought leadership in AI/ML Guide clients in building robust MLOps practices and data-driven cultures Hiring and line-managing data scientists and analysts Security Clearance An increasing number of our customers are specifying a minimum of SC (security check) clearance More ❯

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human More ❯

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human More ❯

Role : Machine Learning Engineer Location : London, UK (Hybrid) Salary : £50k–£65k (DOE) Are you passionate about artificial intelligence, innovation, and building systems with real-world impact? Join a fast-paced innovation team working on cutting-edge compliance technology that integrates More ❯

MLOPS ENGINEER LONDON - HYBRID £80,000 - £95,000 This is a great opportunity for an MLOps engineer from a DevOps background with ML experience to drive cutting-edge work at a data-driven retail tech start-up! ROLE: In this role you will: Design, deploy and scale on their cloud platform (AWS/GCP) Implement and maintain CI/CD … pipelines Engineering data working closely with the Computer Vision team Deploying APIs and packages Stay updated on emerging technologies, trends, and best practices in DevOps and MLOps to recommend and implement innovative solutions that drive business value. Tech stack: Python, AWS/GCP, Docker, CI/CD, Deep Learning, Kubernetes, DevOps REQUIREMENTS: MSc in a numerical or relevant field is … preferred MLOps experience is required An excellent understanding of DevOps processes and techniques Happy working in a fast-paced environment Any experience working with computer vision engineers is a bonus! How To Apply Please register your interest for this role by sending your CV to Joseph Gregory via the apply link on this page. More ❯

cutting-edge machine learning solutions that influence decision-making across a large, fast-moving business. You'll have access to vast datasets, modern tooling, and the support of experienced MLOps and Data Engineering teams – freeing you to focus on model innovation , business impact , and team leadership . Key Responsibilities Lead and coach a team of data scientists focused on pricing … senior stakeholders to prioritise and deliver key initiatives. Work cross-functionally with Marketing and Operations data teams to extend the reach of data science across the organisation. Collaborate with MLOps and Engineering teams to ensure seamless product delivery and integration. Promote the use and value of pricing models to non-technical stakeholders through clear and effective communication. Continuously improve the … flexible hybrid work model (Reading or London) and a collaborative environment. A role where your models directly shape pricing, influence profitability, and deliver real commercial outcomes. Support from seasoned MLOps and engineering teams – letting you focus on research, modelling, and innovation . If you’re passionate about pricing science and ready to step into a leadership role where your work More ❯