176 to 200 of 272 MLOps Jobs in London

ALTEN , an engineering and technology consultancy, We are a leading Engineering and IT consultancy operating across 30 countries, making waves in all sectors: Aeronautics, Space, Defence, Security and Naval, Automotive, Rail and mobility, Energy and environment, Life Sciences and health More ❯

twice a week on-site 6 month initial contract Working with a financial services client who are looking to build a new AI/ML function. Looking for a MLOps Engineer to design, develop and implement AI and ML applications. Will require working cross-functionally to conceptualise, design, test and deploy AI projects. Azure AI/ML Engineer, key responsibilities More ❯

and scales AI, including generative and agentic technologies, end-to-end. Skills and Experience Proven leadership experience in Gen AI delivery Hands-on technical understanding of modern AI tooling, MLOps, and model deployment and generative/agentic AI frameworks Commercial mindset, experience bringing AI, including generative, use cases into production Strong communication skills and the ability to build and scale More ❯

ML models Able to be SC cleared - Must hold British passport (we have MoD projects) There are also some things that would be helpful to have like experience with MLOps and having worked in a startup. What do we offer? Upto £140k base salary Generous share options Flexible and hybrid working – 2 days in office (40 mins from Paddington) Interested More ❯

ML models Able to be SC cleared - Must hold British passport (we have MoD projects) There are also some things that would be helpful to have like experience with MLOps and having worked in a startup. What do we offer? Upto £140k base salary Generous share options Flexible and hybrid working – 2 days in office (40 mins from Paddington) Interested More ❯

but Valuable) Worked at a Pre-Seed or Seed-stage startup through to Series A Built or deployed software used by enterprise customers Experience with applied machine learning or MLOps (not just academic or notebook-based work) Exposure to event-driven architectures, streaming systems (Kafka, etc.), or real-time data pipelines Frontend experience in React, TypeScript, or similar modern frameworks More ❯

including conferences, publications, and industry forums About You • Proven record in AI and machine learning strategy and delivery, ideally within the financial or professional services sector • Strong experience with MLOps and scaling AI applications into production environments • Deep understanding of systems architecture and engineering principles, with experience leading full stack technology teams • Commercial awareness of how AI can drive growth More ❯

including conferences, publications, and industry forums About You • Proven record in AI and machine learning strategy and delivery, ideally within the financial or professional services sector • Strong experience with MLOps and scaling AI applications into production environments • Deep understanding of systems architecture and engineering principles, with experience leading full stack technology teams • Commercial awareness of how AI can drive growth More ❯

twice a week on-site 6 month initial contract Working with a financial services client who are looking to build a new AI/ML function. Looking for a MLOps Engineer to design, develop and implement AI and ML applications click apply for full job details More ❯

Engineers (Junior to Mid-Level) who want to work with the latest in LLMs, co-pilots, agentic workflows, RAGs , and more, while also applying real data science, ML, and MLOps skills in live enterprise environments. What You’ll Do: Work directly with enterprise clients to design and deploy custom AI agents Tackle complex business problems with intelligent, scalable solutions Blend More ❯

Engineers (Junior to Mid-Level) who want to work with the latest in LLMs, co-pilots, agentic workflows, RAGs , and more, while also applying real data science, ML, and MLOps skills in live enterprise environments. What You’ll Do: Work directly with enterprise clients to design and deploy custom AI agents Tackle complex business problems with intelligent, scalable solutions Blend More ❯

and delivering intelligent solutions that solve real business problems at scale. What you’ll bring: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows. Client-facing experience with a forward-deployed engineering mindset. You’ll work directly with More ❯

and delivering intelligent solutions that solve real business problems at scale. What you’ll bring: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows. Client-facing experience with a forward-deployed engineering mindset. You’ll work directly with More ❯

and maintain continuous pipelines: ingest simulation + tele‐op logs, version them, apply weak‐supervision labelling, curate balanced datasets, and auto‐surface fresh failure cases into retraining. Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‐time edge inference. We’re Looking For: 3+ years building deep‐learning systems (industry or research) with shipped More ❯

and maintain continuous pipelines: ingest simulation + tele‐op logs, version them, apply weak‐supervision labelling, curate balanced datasets, and auto‐surface fresh failure cases into retraining. Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‐time edge inference. We’re Looking For: 3+ years building deep‐learning systems (industry or research) with shipped More ❯

Data Science Engineer - MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL We are actively working with a global law firm who are actively looking to bolster their IT team as they undergo a global-scale cloud transformation. At present they are looking to take on a new Data Science Engineer (MLOPS, Machine Learning … tier global law firm who have a long-stream of projects in the pipeline alongside a diverse and collaborative team environment. To be considered for this Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) role, it's ideal you have: Ideal but not required law firm experience 2-4 years … science and AI solutions end-to-end, from design and development through testing, release, monitoring, and support. Operationalize models with CI/CD pipelines, automated testing, and monitoring, applying MLOps practices such as versioning, retraining, and drift detection (tools: MLflow, Azure ML, Databricks) Leverage both open-source frameworks (LangChain, Hugging Face, etc.) and enterprise platforms (Azure OpenAI, Databricks, etc.) to More ❯

large (AI) transformational journeys BCG does for its clients. Often involves the following engineering disciplines : Cloud Engineering Data Engineering (not building pipelines but designing and building the framework) DevOps MLOps/LLMOps Often work with the following technologies : Azure, AWS, GCP Airflow, dbt, Databricks, Snowflake, etc. GitHub, Azure DevOps and related developer tooling and CI/CD platforms, Terraform or … other Infra-as-Code MLflow, AzureML or similar for MLOps; LangSmith, Langfuse and similar for LLMOps The difference to our "AI Engineer" role is: Do you "use/consume" these technologies, or are you the one that "provides" them to the rest of the organization. What You'll Bring TECHNOLOGIES: Programming Languages: Python Experience with additional programming languages is a More ❯

/knowledge: Experience in architecting and solutioning in Gen AI, Agentic AI, classic ML, and automation space. Good understanding of Prompt engineering, RAG pipelines, Supervised/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability. Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS, etc.). Ability to … services. Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems. Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). More ❯

/knowledge: Experience in architecting and solutioning in Gen AI, Agentic AI, classic ML, and automation space. Good understanding of Prompt engineering, RAG pipelines, Supervised/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability. Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS, etc.). Ability to … services. Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems. Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Deep proficiency in Python and extensive experience with relevant AI/ML/NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK). More ❯

deployed systems; Hands-on experience with sensor selection, placement, and calibration. Expertise in training and fine-tuning models for perception in novel or domain-shifted environments; Solid foundation in MLOps, including dataset management, training infrastructure, and deployment pipelines. Nice to have: Experience in construction robotics, heavy machinery, or large-scale manipulation tasks. Familiarity with vision-language models and their use More ❯

deployed systems; Hands-on experience with sensor selection, placement, and calibration. Expertise in training and fine-tuning models for perception in novel or domain-shifted environments; Solid foundation in MLOps, including dataset management, training infrastructure, and deployment pipelines. Nice to have: Experience in construction robotics, heavy machinery, or large-scale manipulation tasks. Familiarity with vision-language models and their use More ❯

data ecosystem. You’ll be the technical lead for machine learning and AI engineering — building production-ready systems, enabling seamless collaboration with data scientists, and shaping the long-term MLOps strategy. Beyond implementation, you’ll play a pivotal role in defining how advanced analytics supports smarter decision-making, better customer experiences, and more sustainable operations across the business. What You … and high performing. Work hand-in-hand with data scientists to design, prototype, and operationalize ML and AI models that deliver real business value. Develop and maintain a comprehensive MLOps framework — from versioning and CI/CD to monitoring and governance. Provide technical guidance and mentorship, helping grow a capable ML Engineering team over time. Partner with product, platform, and … can translate technical complexity into business value. Proven experience in classical machine learning, with hands-on expertise in model development, optimisation, and deployment. Deep understanding of ML Engineering and MLOps principles (cloud-based pipelines, CI/CD, monitoring, reproducibility). Experience with Python, SQL & Azure (AWS & GCP is also fine). Exposure to GenAI or LLM tools and frameworks is More ❯

data ecosystem. You’ll be the technical lead for machine learning and AI engineering — building production-ready systems, enabling seamless collaboration with data scientists, and shaping the long-term MLOps strategy. Beyond implementation, you’ll play a pivotal role in defining how advanced analytics supports smarter decision-making, better customer experiences, and more sustainable operations across the business. What You … and high performing. Work hand-in-hand with data scientists to design, prototype, and operationalize ML and AI models that deliver real business value. Develop and maintain a comprehensive MLOps framework — from versioning and CI/CD to monitoring and governance. Provide technical guidance and mentorship, helping grow a capable ML Engineering team over time. Partner with product, platform, and … can translate technical complexity into business value. Proven experience in classical machine learning, with hands-on expertise in model development, optimisation, and deployment. Deep understanding of ML Engineering and MLOps principles (cloud-based pipelines, CI/CD, monitoring, reproducibility). Experience with Python, SQL & Azure (AWS & GCP is also fine). Exposure to GenAI or LLM tools and frameworks is More ❯

integrating with live data feeds and cloud infrastructure. Research and prototype cutting-edge AI techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data … analytics TO BE CONSIDERED Please apply directly by emailing with your CV and availability. KEYWORDS: AI Engineer, Machine Learning Engineer, Sports Analytics, Computer Vision, Deep Learning, Python, TensorFlow, PyTorch, MLOps, Data Science, Predictive Modelling, Sports Tech, AI in Sports More ❯

integrating with live data feeds and cloud infrastructure. Research and prototype cutting-edge AI techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data … BE CONSIDERED... Please apply directly by emailing jordanna.ramsey@searchability.com with your CV and availability. KEYWORDS: AI Engineer, Machine Learning Engineer, Sports Analytics, Computer Vision, Deep Learning, Python, TensorFlow, PyTorch, MLOps, Data Science, Predictive Modelling, Sports Tech, AI in Sports More ❯