22 of 22 MLOps Jobs in the City of London

experimentation, pragmatic engineering, and rapid iteration are key to creating business value. Leverage modern tools and methods: Use contemporary ML frameworks, cloud platforms, and MLOps best practices to build scalable, reusable solutions. Communicate insights clearly: Distill complex technical findings into concise, actionable narratives for technical and business audiences alike. Keep ...

testing, and statistical evaluation. Proven track record transitioning models from experimentation to production with governance and quality controls. Experience with experiment tracking and MLOps tooling (MLflow, Weights & Biases, DVC). Experience developing LLM/GenAI applications, including prompt engineering and RAG architectures. Familiarity with LLMOps tooling (LangSmith, LangChain, LangGraph). ...

security clearance; sponsorship cannot be provided. Desirable: Knowledge of AWS services (e.g., Lambda, ECS, Bedrock, S3, SageMaker). Experience with ML engineering and MLOps (e.g., Docker, MLflow). Experience in regulated industries or government-related projects. Applying LLMs or advanced AI methods to real-world problems. Benefits: Competitive salary ...

Services, and Azure Machine Learning. Familiarity with Azure Databricks is a plus. Understanding of CI/CD pipelines, containerization (Docker, Kubernetes), and experience implementing MLOps practices using Azure DevOps. Qualifications such as the following would be advantageous, however not necessary: Microsoft Azure AI Engineer Fundamentals/Associate Microsoft Azure Data ...

growth. Oversee the design, training, and deployment of search and recommendation models — from data strategy to monitoring and performance optimisation. Collaborate with platform and MLOps teams to ensure robust, efficient, and scalable ML workflows (including CI/CD, feature management, and monitoring). Share insights and best practices across other ...

PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research in machine learning are also beneficial. Experience configuring and maintaining cloud infrastructure including network infrastructure, compute, access control policies, load balancers, Public ...

transformer architectures and attention mechanisms . Experience deploying AI applications on cloud platforms (AWS, Azure, GCP) and containerisation tools (Docker, Kubernetes). Knowledge of MLOps , evaluation metrics for LLMs, and implementing responsible AI principles . Experience in Insurtech or Fintech domains. Desirable Familiarity with insurance workflows or policy administration systems. ...

orchestration, and agentic architectures Proven experience delivering ML/AI systems into production environments Excellent Python engineering and system design skills Familiarity with APIs, MLOps, and cloud deployment (AWS, GCP, or Azure) Clear communicator, comfortable in fast-paced, early-stage environments STEM degree required; MSc in AI, Computer Science ...

Large Language Models (LLMs) for text analysis, sentiment analysis, and generative AI applications. Build and maintain production-grade ML pipelines using CI/CD, MLOps, and cloud platforms (Azure, AWS, GCP). Conduct A/B testing and randomized control trials to validate model performance and business impact. Perform data … Expertise in NLP techniques and frameworks, familiarity with LLM fine-tuning and deployment. Knowledge of big data technologies and cloud platforms. Strong understanding of MLOps practices, CI/CD pipelines, and model monitoring tools . Proficiency in data visualization tools. Excellent problem-solving skills, attention to detail, and ability ...

coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming ...

Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 About the Company Our client is an extremely well know, digital marketplace focused on sustainable ecommerce. With over 35 million of active users globally, they’re redefining how people … opportunity, and flexible working. They offer a progressive benefits package designed to support wellbeing, learning, and work-life balance. The role of Engineering Manager, MLOps, Marketplace, Ecommerce, | 35 Million Users | UK Remote OR London, Hybrid, 1 Day PW, Up to £140,000 Our Client is looking for an experienced MLOps ...

work from home. The AI Engineer will support delivery of AI use cases, workflows, analytics and solutions - responsible for tasks such as pattern recognition, MLOps, software development, neural networks, and natural language processing on a day-to-day basis. Qualifications Pattern Recognition and Neural Networks skills Computer Science and Software ...

building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation metrics, hyperparameter tuning, feature engineering, and MLOps practices for production deployment. Generative AI & LLM Integration - Proficient in working with Large Language Models including OpenAI GPT models, Anthropic Claude, Azure OpenAI, and open … databases (SQL Server), data validation, cleansing workflows, scheduling tools (Azure Data Factory), and ensuring data quality for machine learning applications. Machine Learning Operations (MLOps) - Experience deploying ML models to production environments using containerisation (Docker), orchestration (Kubernetes), model versioning (MLflow, DVC), monitoring model performance and drift, A/B testing frameworks ...

Azure OpenAI, Prompt Engineering, Cognitive Search, Form Recognizer. Data/Coding: Expert-level Python, PySpark, and Vector DB integration. Ops: Practical knowledge of MLOps and LLMOps lifecycles. Security: Must hold active UK Government SC Clearance. Certifications Mandatory: AZ-204 (Azure Developer Associate). Preferred: AZ-305 (Solutions Architect ...

learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall, F1, Intersection over Union, and others. Additional beneficial ...

frameworks (e.g., LangGraph, PydanticAI) and managing memory and tool-calling in production. Engineering Mindset : Ability to write clean, testable Python and familiarity with modern MLOps stacks. Product Experience : Experience shipping ML systems in production for real users, with an experimental mindset and high bar for AI ethics. Why Join Wilgot ...

deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities * End-to-end development of AI/ML solutions. * MLOps practices: CI/CD, model monitoring, retraining. * Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). * Generative AI features: embeddings, RAG, AI agents. …/ML delivery. * Legal/professional services experience is a plus. * AI/ML frameworks: PyTorch, TensorFlow, LangChain. * Cloud: Azure (preferred), AWS, GCP. * MLOps: CI/CD, model lifecycle, monitoring. * Generative AI: LLMs, RAG, chat agents. * Data engineering alignment: ETL, governance. * Strong coding, communication, and collaboration skills. * Strategic thinking, problem ...

from the Ultralytics export toolkit . Knowledge of cloud AI services and training infrastructure across AWS, Google Cloud, and Azure, including GPU clusters and MLOps considerations. Proven ability to lead benchmarking, technical validation, and co-development programs using our benchmark capabilities and integration best practices. Strong ability to connect technical ...

Role - Senior Lead Analyst- Data Scientist Technology – Data science, MLops, GenAI Location – London, UK Job Description Today, the corporate landscape is dynamic, and the world ahead is full of possibilities! None of the amazing things we do at Infosys would be possible without an equally amazing culture, the environment where … leadership roles with team management. •Strong expertise in Azure Machine Learning, Python, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. •Design and implement ML pipelines on Azure Machine ...

create real commercial leverage Skills and Experience Proven leadership in defining and delivering enterprise AI strategy, including GenAI Strong understanding of AI platforms, MLOps, and modern AI tooling (without needing to be hands-on) Experience translating AI opportunities into commercially impactful use cases at scale Exceptional communication, influence, and stakeholder ...

FastAPI , especially in serverless environments (e.g., Google App Engine) Streaming Data: Familiarity with real-time data pipelines and data ingestion at scale DevOps/MLOps: Exposure to Terraform , Docker , Kubernetes , and MLOps workflows What They Offer A chance to work on real-world data that impacts elite football performance Access ...

Strong Python; exposure to AWS, Docker, Terraform/CDK, etc. • Experience with basic web computing constructs: APIs, authentication, etc. • Solid grounding in ML algorithms, MLOps, and data science. • Ability to work with customers/stakeholders to help them achieve their goals. • Willingness and ability to travel to customer offices globally … occasionally exceed 50% if required). Nice-to-Have: • Built agentic workflows/LLM tool-use. • Experience with MLFlow, Arize, LangFuse, or other MLOps tools. • Experience with deploying ML models on SageMaker, KServe, or similar. Why Plexe? • Hard problems: we're automating the entire ML/AI lifecycle from data ...