176 to 200 of 284 MLOps Jobs in London

teams and delivering complex software platforms and AI-native products. Deep expertise in Generative AI, Deep Learning, Reinforcement Learning, ML fundamentals, end-to-end MLOps, AI infrastructure, and proficiency with frameworks like PyTorch. Active interest and experience in multi-agent systems, collective learning, AI safety, secure agent execution, emerging AI More ❯

labs, GPU buyers, DevOps teams, or enterprise R&D Familiarity with cloud-native technologies, LLM infrastructure, or ecosystem players like NVIDIA, Hugging Face, or MLOps vendors Background in partner or channel marketing Working knowledge of SEO, SEM, and campaign analytics Benefits Competitive total compensation package (cash + equity). Retirement More ❯

labs, GPU buyers, DevOps teams, or enterprise R&D Familiarity with cloud-native technologies, LLM infrastructure, or ecosystem players like NVIDIA, Hugging Face, or MLOps vendors Background in partner or channel marketing Working knowledge of SEO, SEM, and campaign analytics Benefits Competitive total compensation package (cash + equity). Retirement More ❯

labs, GPU buyers, DevOps teams, or enterprise R&D Familiarity with cloud-native technologies, LLM infrastructure, or ecosystem players like NVIDIA, Hugging Face, or MLOps vendors Background in partner or channel marketing Working knowledge of SEO, SEM, and campaign analytics Benefits Competitive total compensation package (cash + equity). Retirement More ❯

about data and its ability to empower and improve lives. Work with cross-functional teams to deliver production level ML/AI solutions. Implement MLOps with a focus on versioning and data security. Champion Machine Learning across the business. Mentor junior members of the team. Profit share bonus. Skills and More ❯

Build and maintain robust pipelines for model training, validation, deployment, and monitoring Act as a trusted technical advisor, understanding client challenges and designing tailored MLOps solutions Collaborate with internal teams and clients to translate business needs into practical, scalable AI solutions Optimise the performance and reliability of models running in More ❯

model pipeline engineering, thrives in a collaborative cross-functional team, and wants to grow while gaining exposure to innovative tooling in the LLM and MLOps space Main Purpose of Role LLM/NLP Production Engineering Build and maintain scalable, production-ready pipelines for Natural Language Processing and Large Language Model … ML models and prompt-based LLM workflows using containerised services. Ensure reliable model integration across real-time APIs and batch processing systems. Pipeline Automation & MLOps Use Apache Airflow (or similar) to orchestrate ETL and ML workflows. Leverage MLflow or other MLOps tools to manage model lifecycle tracking, reproducibility, and deployment. … work from home, in the office or remotely. Who is best suited to this role? 2-3 years of experience in ML engineering or MLOps/LLMOps. Strong Python programming skills for data manipulation and pipeline development. Hands-on experience with containerisation using Docker and Kubernetes. Proven experience deploying ML More ❯

include analyzing client requirements, managing the ML lifecycle from data collection and model design to deployment and monitoring, and collaborating with data scientists and MLOps engineers to implement models into production. Data Reply offers extensive training and a clear learning path, with opportunities to participate in hackathons, code challenges, and … pipelines for training and deploying models. Implement solutions to monitor model performance in production. Work with cross-disciplinary teams including Data Engineers, Data Scientists, MLOps Engineers, and Data Visualization Specialists. Engage with domain experts to understand and address complex problems. Analyze and communicate client data insights to stakeholders. About the More ❯

in collaboration with Databricks’ professional services team. This is a hands-on technical leadership role where you’ll combine deep machine learning knowledge with MLOps best practices to deploy scalable, high-performing models across varied domains. You’ll lead delivery squads, guide solution architecture, liaise with stakeholders and ensure our … Azure, or GCP) Translate business problems into robust ML solutions through a blend of statistical modelling, machine learning, and data engineering Apply and champion MLOps practices throughout the model lifecycle—training, versioning, monitoring, and retraining Collaborate with client teams and internal stakeholders to deliver on business-critical initiatives Mentor and More ❯

in collaboration with Databricks’ professional services team. This is a hands-on technical leadership role where you’ll combine deep machine learning knowledge with MLOps best practices to deploy scalable, high-performing models across varied domains. You’ll lead delivery squads, guide solution architecture, liaise with stakeholders and ensure our … Azure, or GCP) Translate business problems into robust ML solutions through a blend of statistical modelling, machine learning, and data engineering Apply and champion MLOps practices throughout the model lifecycle—training, versioning, monitoring, and retraining Collaborate with client teams and internal stakeholders to deliver on business-critical initiatives Mentor and More ❯

in collaboration with Databricks’ professional services team. This is a hands-on technical leadership role where you’ll combine deep machine learning knowledge with MLOps best practices to deploy scalable, high-performing models across varied domains. You’ll lead delivery squads, guide solution architecture, liaise with stakeholders and ensure our … Azure, or GCP) Translate business problems into robust ML solutions through a blend of statistical modelling, machine learning, and data engineering Apply and champion MLOps practices throughout the model lifecycle—training, versioning, monitoring, and retraining Collaborate with client teams and internal stakeholders to deliver on business-critical initiatives Mentor and More ❯

large language models and multi-modal models for targeted use cases, ensuring high performance and low latency in production. Implement distributed training and scalable MLOps pipelines for continuous model improvement Collaborate with cross-functional teams-research, product, and engineering-to embed AI capabilities into products and services Evaluate and select … to integrate these processes into scalable pipelines Experience deploying AI models and full-stack applications using cloud-native tools Strong grasp of DevOp/MLOps best practices, including version control and CI/CD Excellent problem-solving, debugging and rapid prototyping Strong project management skills to coordinate effectively with technical More ❯

Title: Senior Data Scientist, Media Optimization Location: London Reporting to: VP, Data Science, Optimization Who we are: Choreograph is WPP's global data products and technology company. We're on a mission to transform marketing by building the fastest, most More ❯

Aventis Solutions has partnered with a high-growth technology team seeking a Head of Data Science to lead and scale a world-class data science function across their global business. This is a unique opportunity to shape the data science More ❯

Aventis Solutions has partnered with a high-growth technology team seeking a Head of Data Science to lead and scale a world-class data science function across their global business. This is a unique opportunity to shape the data science More ❯

Are you excited about working at the forefront of applied research in an industry setting? Thomson Reuters Labs is seeking scientists with a passion for solving problems using state-of-the-art machine learning, natural language processing and generative AI. More ❯

with the communities in which we work and live. It is personal to all of us." - Julie Sweet, Accenture CEO As an Manager in MLOps you will: Be engaged at the forefront of technological advancements in GenAI and expected to keep up to date with latest trends Set up the … the day-to-day technical engagements on a project, helping to manage a small team Be the go-to technical expert for all things MLOps Contribute to improving life at Accenture and the wider department by raising your voice and engaging - we want to hear your views! Performance manage a More ❯

level work. Required Skills and Attributes: 7 years or more of coding experience, with at least 3 years primarily focused on Python. Knowledge of MLOps principles and practices, especially in implementing them within production settings. Worked on cloud infrastructure (AWS, Azure, GCP) Worked on data-intensive products which are heavy More ❯

The ideal candidate will have a strong background in Machine Learning engineering and an expert in operationalising models in the Databricks MLFlow environment (chosen MLOps Platform). Responsibilities: Collaborate with Data Scientists and operationalise the model with auditing enabled, ensure the run can be reproduced if needed. Implement Databricks best More ❯

Proven capability working with PySpark and distributed data processing Experience building and deploying solutions using Microsoft Copilot and related M365 AI tools Familiarity with MLOps principles and tools (model deployment, monitoring, CI/CD pipelines) Ability to work across multiple stakeholders and translate business requirements into AI-driven solutions Bonus More ❯

capability working with PySpark and distributed data processing Experience designing and advising on solutions using Microsoft Copilot or other M365 AI tools Familiarity with MLOps principles and tooling such as CI/CD pipelines, model monitoring, and deployment Ability to collaborate across multiple stakeholders and translate business needs into scalable More ❯

practice and drive improvements across our ML operations. The ideal candidate will have the following skills and experience: An appreciation of good architecture and MLOps best practice The ability to collaborate with, and influence, technical and non-technical people A passion for end-to-end ownership of solutions, from articulation 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 … 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 More ❯

SENIOR MACHINE LEARNING ENGINEER - MLOPS REMOTE (Travel to London once per month) Up to £80,000 COMPANY: We are working with a leading telecoms/mobile network who 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 them move models from More ❯

SENIOR MACHINE LEARNING ENGINEER - MLOPS REMOTE (Travel to London once per month) Up to £80,000 COMPANY: We are working with a leading telecoms/mobile network who 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 them move models from More ❯