1 to 25 of 147 MLOps Jobs in the UK excluding London

LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). • Familiarity with on-device or edge-AI deployments (e.g., TensorFlow Lite, ONNX, mobile/embedded inference). • Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. • Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL More ❯

measurement. Collaborative Development: Work closely with marketing strategists, data analysts, data engineers, and product owners to define use cases and deliver scalable solutions. Model Deployment & Monitoring: Deploy models using MLOps practices and tools (e.g., MLflow, Airflow, Docker, cloud platforms) ensuring performance, reliability, and governance compliance. Innovation & Research: Stay current on advancements in AI/ML and proactively bring forward new More ❯

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 ❯

positive change and use AI for good. We are growing our team of engineers to help deliver an increasing number of client projects. You won't need an existing MLOps background to apply for this role. You'll learn as you go by immersing yourself in this exciting new field. What we're looking for We've seen considerable growth … over the past few years and this will continue as we build on our reputation as Open Source MLOps experts, while working with the community, and delivering solutions to our clients. The ideal candidate would be motivated to grow and progress in line with the company's ambitions. As well as being a great engineer, motivated by the chance to … be at the forefront of MLOps adoption, you'll also enjoy being part of a culture that values: Loving what we do: a real passion for Open Source, MLOps and taking pride in great work. Just trying it: MLOps is an exciting new field. We love to develop new skills, solve new problems and thrive on a challenge. Being greater More ❯

testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organizational skills to our team and help us drive innovation and excellence. This is a flexible … Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic … services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic More ❯

testing, validation, deployment, to monitoring and retraining of models within different environments. If you've a strong understanding of Microsoft Azure, fluency in data science coding, and expertise in MLOps frameworks, we want to hear from you. Bring your excellent communication, problem-solving, and organizational skills to our team and help us drive innovation and excellence. This is a flexible … Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic … services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot problems quickly Excellent problem-solving and analytic More ❯

operations throughout the United States as well as in Belfast. For more information, visit DailyPay's Press Center. The Role: We are seeking a highly skilled and motivated Senior MLOps Engineer to join our growing team in Belfast. You will play a crucial role in maturing and scaling our machine learning infrastructure and processes, ensuring the reliability, scalability, and performance … of our ML models in production. This role requires a strong background in MLOps principles, cloud technologies (AWS), and a passion for building robust and efficient systems. You will collaborate closely with data scientists, engineers, and product teams to deliver high-quality ML solutions that directly impact our business. The mission of the Data Science Team is critical for the … development and success of our product, understanding the needs of our customers and partners, and maintaining DailyPay's leading role in the early wage access industry. As a staff MLOps Engineer, you will be instrumental in helping to realize this vision for DailyPay by enabling efficient and effective deployment and management of machine learning models. How You Will Make an More ❯

in structured data querying and 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. Develop and maintain data integration … LangGraph, including prompt engineering, fine-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 model performance evaluation, hyperparameter tuning 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 ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

and deploy advanced machine learning and behavioural intelligence models. Lead the transition of prototypes into scalable, cloud-native production systems. Architect data pipelines and model-serving infrastructure (Docker, Kubernetes, MLOps). Work with large-scale time series and behavioural data from diverse sensors. Contribute to strategic technical decisions and mentor junior engineers. Collaborate cross-functionally with product, UX, and leadership … Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS/GCP/Azure. Hands-on with MLOps, CI/CD for ML, and model performance monitoring. A background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A More ❯

attribution, predicting customer propensity, segmenting customer groups based on behavioural data, and recommending products and/or content. Fine-tune Large Language Models to business-specific use cases. Deploy MLOps pipelines together with our ML engineers. Work closely with data engineers, fellow data scientists/AI engineers and consultants to ensure seamless integration and deployment of AI solutions that create … communication and problem-solving skills. Direct availability to start working in the UK. Nice to have: Experience with natural language processing (NLP) or computer vision (CV). Knowledge of MLOps and model deployment pipelines. Familiarity with AI ethics and responsible AI principles. Experience working with large datasets and distributed computing. Contributions to open-source AI projects. WE OFFER: The benefits More ❯

team helping to 'walk in the shoes' of application teams as well as operational engineering teams. Communicate progress, results, and insights to management and other stakeholders. Strong understanding of MLops principles and practices. Daily/Monthly Responsibilities Build and run responsibilities for GenAI ensuring robust support folding into standard incident processes as the products mature. Help work with distributed teams … and LLMs. An overall 8+ years of experience as Software Engineer. Proficiency in programming languages such as Python, TensorFlow, PyTorch, and other AI/ML frameworks. Strong understanding of MLops principles and practices. Ability to design and implement complex ML systems. Strong understanding of neural networks, natural language processing (NLP), computer vision, and other AI domains. Experience with cloud platforms More ❯

and Computer Vision Take ownership of developing, training and productionising machine learning lifecycles, adhering to best practices, security needs and quality assurance Development of neural networks Implementing and maintaining MLops workflows Work alongside Data Engineers and DevOps Engineers to ensure continuous integration and deployment of machine learning models in production. Proactive learning and researching new technologies and software versions Working … Knowledge of machine learning architectures, loss functions, tools and techniques Experience training machine learning models, including hyperparameter tuning and optimizing model performance Experience with (or at least exposure to) MLops workflows Experience with Python Experience with SQL Critical thinking and ability to problem solve Experience with data warehousing and database systems Exposure to working with CI/CD Knowledge of More ❯

60k per annum As a Machine Learning Engineer , you will be part of an MLOps team, working alongside data scientists, software engineers, and other stakeholders to bring machine learning models to life. You will be responsible for deploying, maintaining, and monitoring models in production, improving model performance, and refining the machine learning infrastructure to support business objectives. Your role will More ❯

tools and cloud platforms (e.g., Azure, GCP, AWS) Knowledge of deep learning, NLP, and computer vision techniques, (especially in the context of Microsoft Copilot and OpenAI APIs) Familiarity with MLOps practices using tools like Azure ML Pipelines, MLflow, Docker, and Kubernetes Excellent problem-solving and analytical skills, with the ability to apply AI to legal challenges Bachelor's or master 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 ❯

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. Proficient in designing and implementing MLOps/LLMOps pipelines for model deployment, monitoring, version control, and CI/CD workflows. Strong understanding of model performance evaluation, hyperparameter tuning, and maintenance using tools like Vertex AI Pipelines. 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 Engineers for a fast-growing tech start-up at the … mission-critical domains. You’ll 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) Work with tools like Terraform … Collaborate on high-impact, real-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 For Most importantly, you must More ❯

changes. We welcome open-minded 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 science and R&D teams … ML systems for performance, errors, 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 cloud environments. Proficiency 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 ❯

and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow More ❯

and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow More ❯

with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯