176 to 200 of 337 MLOps Jobs in the UK

anomaly detection to discover patterns and trends in large datasets. Analyze and preprocess large datasets to extract meaningful insights and features for model training MLOps - Deployment into production environments, Monitoring and Maintenance Experience deploying and maintaining large-scale ML inference pipelines into production Implement and monitor model performance in production … Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale ML inference pipelines into production environments. Proficiency with Docker for containerization and Kubernetes for orchestration. Familiarity with AWS More ❯

MLOps Engineers (Mid, Senior & Lead level) – UKIC DV Cleared | AI/ML Start-up | Manchester | Hybrid Are you an MLOps Engineer with active UKIC DV clearance looking to make a real-world impact at the cutting edge of AI and machine learning? We’re hiring Mid, Senior, and Lead MLOps … play a key role in designing and deploying robust ML infrastructure, supporting both public and private sector clients. What You'll Do as an MLOps Engineer: Deploy and manage machine learning models in production environments Build and optimise scalable MLOps pipelines using modern tools and cloud platforms (AWS, Azure, GCP … world AI/ML projects that truly make a difference Contribute ideas in a relaxed, open, and innovation-driven culture Location & Flexibility for the MLOps Engineer: Hybrid role based in Manchester Strong work-life balance and a genuinely fun, inclusive environment Excellent career progression , bonus structure What We're Looking More ❯

experience building APIs supporting analytics, research, or actuarial functions in an insurance environment. Proficiency with cloud technologies such as Snowflake, Databricks, and familiarity with MLOps frameworks. Exhibit strong collaboration, problem-solving, and communication skills, with the ability to adapt to changing priorities and simplify complex problems. More ❯

experience building APIs supporting analytics, research, or actuarial functions in an insurance environment. Proficiency with cloud technologies such as Snowflake, Databricks, and familiarity with MLOps frameworks. Exhibit strong collaboration, problem-solving, and communication skills, with the ability to adapt to changing priorities and simplify complex problems. More ❯

model training and evaluation that power transformative healthcare applications. Collaborating closely with Data Scientists and Engineers, you'll produce advanced AI solutions while optimizing MLOps processes to drive efficiency and impact. The ideal candidate will bring experience as a Machine Learning Engineer or Data Scientist, preferably within the healthcare, biotech More ❯

API integration. Hands-on experience with AI services such as Azure Cognitive Services, Google AI, or OpenAI. Familiarity with data pipelines, model deployment, and MLOps is a plus. Excellent stakeholder communication skills and the ability to explain complex technical topics to non-technical audiences. Strong problem-solving mindset and the More ❯

/other IAC Deep familiarity with Linux SRE experience (on-calls, incident management, post-mortems) Nix, ideally with custom derivations, Flakes, and cross-building MLOps/data pipelines Experience with Kubernetes Experience running in AWS ECS in production Just state the word 'Salmon' anywhere in your application, just to prove More ❯

/other IAC Deep familiarity with Linux SRE experience (on-calls, incident management, post-mortems) Nix, ideally with custom derivations, Flakes, and cross-building MLOps/data pipelines Experience with Kubernetes Experience running in AWS ECS in production Just state the word 'Salmon' anywhere in your application, just to prove More ❯

At JFrog, we're reinventing DevOps, DevSecOps and MLOps to help the world's greatest companies innovate, develop faster and be more secure and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here More ❯

industry advancements and emerging AI applications. 🔹 Collaborate with external partners, including other government agencies and industry bodies. 🔹 Provide technical leadership on machine learning deployment, MLOps, and model performance monitoring . Key Requirements ✅ Expertise in Data Science & Machine Learning , including supervised/unsupervised learning, deep learning, and generative AI. ✅ Strong understanding More ❯

cloud automation and orchestration using tools such as CloudFormation or Terraform Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving - Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining - Set up model drift More ❯

and a direct role in delivering both capital and business-as-usual (BAU) projects on time and within budget. Experience in Machine Learning Operations (MLOps) and AI is a plus. KEY ACCOUNTABILITIES Drive simple, standardized, and innovative ways to ingest, process, store, and analyze various data sources Design, implement, and More ❯

GCP). Familiarity with cloud-native data architectures and technologies. Experience with data management tools and processes. Experience with AI and Machine Learning, including MLOps practices. Experience with decentralised Data Mesh and Data Product architecture principles. What you will be doing 1 month Collaborate with key stakeholders (product managers, engineers More ❯

models to power AI-driven products. Design and operate large-scale ML systems, including LLM gateways, batch inference pipelines, and RAG-powered applications. Drive MLOps and LLMOps best practices across the organization, ensuring scalability, reliability, and efficiency. Lead the development of custom LLM architectures, pre-training strategies, and cost optimization More ❯

models to power AI-driven products. Design and operate large-scale ML systems, including LLM gateways, batch inference pipelines, and RAG-powered applications. Drive MLOps and LLMOps best practices across the organization, ensuring scalability, reliability, and efficiency. Lead the development of custom LLM architectures, pre-training strategies, and cost optimization More ❯

other business-specific applications. Integrate LLMs with structured data systems (e.g., SQL databases, BigQuery, GCS) to enable natural language querying and advanced analytics. Implementing MLOps/LLMOps pipelines for deploying LLMs in production, monitoring their performance, and ensuring scalability. Evaluating LLM performance, optimising hyperparameters, and ensuring alignment with business objectives. … tuning, and workflow orchestration. Skilled in integrating LLMs with structured data systems (e.g., SQL databases, BigQuery) to enable natural language querying and advanced analytics. MLOps/LLMOps Proficient in designing and implementing MLOps/LLMOps pipelines for model deployment, monitoring, version control, and CI/CD workflows. Strong understanding of More ❯

Job Title: MLOps + DevOps (Platform) Engineer Location: Remote/Hybrid Job Type: Full-time About the Role Chapter 2 is working with a leading creative agency to develop scalable machine learning platforms for AI-driven content creation. This role is perfect for an MLOps + DevOps Engineer who thrives … performance for inference and training across GPUs and cloud-based architectures. Ensure security and compliance for ML platforms handling sensitive data. Evaluate and integrate MLOps tools (MLflow, Kubeflow, etc.) to enhance efficiency. Implement monitoring and alerting systems to detect anomalies and maintain model reliability. What We’re Looking For 3+ … years of experience in software engineering, infrastructure, or MLOps roles. Proven expertise in building and maintaining ML platforms at scale. Hands-on experience with cloud platforms (AWS, GCP, or Azure) for ML workloads. Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation). Solid programming skills in Python and More ❯

Job Title: MLOps + DevOps (Platform) Engineer Location: Remote/Hybrid Job Type: Full-time About the Role Chapter 2 is working with a leading creative agency to develop scalable machine learning platforms for AI-driven content creation. This role is perfect for an MLOps + DevOps Engineer who thrives … performance for inference and training across GPUs and cloud-based architectures. Ensure security and compliance for ML platforms handling sensitive data. Evaluate and integrate MLOps tools (MLflow, Kubeflow, etc.) to enhance efficiency. Implement monitoring and alerting systems to detect anomalies and maintain model reliability. What We’re Looking For 3+ … years of experience in software engineering, infrastructure, or MLOps roles. Proven expertise in building and maintaining ML platforms at scale. Hands-on experience with cloud platforms (AWS, GCP, or Azure) for ML workloads. Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation). Solid programming skills in Python and More ❯

We're a transformation consultancy and we exist to reimagine how enterprises operate, making data and AI their competitive advantage. We turn enterprises into data-driven and AI enabled organisations, unleashing business growth and accelerating outcomes. We have big ambitions More ❯

developers who like to share knowledge and help each other to push Optimove forward using the cutting edge of today's tech. The new MLOps team will be responsible for the seamless deployment, monitoring, and maintenance of machine learning models in production. Acting as the critical link between the data … and drift. Automate infrastructure provisioning and deployment using IaC tools. Collaborate with team leader to define technical strategies. Requirements: 4+ years of experience in MLOps, DevOps, or software engineering roles. Strong programming skills in Python and familiarity with ML frameworks. Extensive experience with AWS services (e.g., SageMaker, ECS, Lambda) and 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 ❯

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 ❯

wide range of AI models which underpin our platform. This includes specific expertise in emerging methods for Graph based model and NLP models. Our MLOps team is tasked with automating and maximizing efficiency of the build, deployment and maintenance of all model types. We are seeking a senior MLOps Engineer … to join our team. This individual will play a crucial role in designing, deploying, and maintaining production-level machine learning models. The Senior MLOps Engineer will focus on leading MLOps initiatives, including infrastructure, automation, and ensuring models are seamlessly transitioned from development to production. What do I need to have … beneficial: Experience deploying machine learning models into production, including managing their lifecycle Experience implementing model governance e.g. model versioning, drift reporting etc. Experience with MLOps tools such as MLFlow, Kubeflow, or DVC Experience with distributed processing systems like Spark (Scala and PySpark would be invaluable) Experience in programming with Scala More ❯

Demonstrates a deep understanding and practical experience in developing and deploying AI models. Design and architect end-to-end AI/ML solutions. Utilize MLOps methodologies to streamline the development, deployment, and monitoring of machine learning models. Experience in Cognitive AI techniques such as NLP, Computer vision, Speech & Conversational AI. More ❯

Demonstrates a deep understanding and practical experience in developing and deploying AI models. Design and architect end-to-end AI/ML solutions. Utilize MLOps methodologies to streamline the development, deployment, and monitoring of machine learning models. Experience in Cognitive AI techniques such as NLP, Computer vision, Speech & Conversational AI. More ❯