76 to 100 of 1,206 MLOps Jobs in the UK

and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. Experience working with large-scale MLOps pipelines, working with and deploying models to production services. About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most More ❯

and associated regulatory requirements. Exposure to healthcare data standards (CDISC, HL7, FHIR, SNOMED CT, OMOP, DICOM). Exposure to big data technologies and handling. Knowledge of machine learning operations (MLOps) and model deployment. Strong problem-solving and analytical abilities. Excellent communication skills for collaborating with stakeholders. Experience working in an Agile development environment. Required/Preferred Education Bachelor’s Degree More ❯

and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc. Experience working with large-scale MLOps pipelines, working with and deploying models to production services. ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most More ❯

cleaning and ML validation strategies. Scalable Solutions: Building training pipelines and components to ensure scalable ML solutions, address errors, and provide education to upskill teams working on ML, enhancing MLOps proficiency. We offer a flexible hybrid working model with 2 days from home and 2-3 days at our central London office, where you'll collaborate with digital specialists and More ❯

of git Experienced in deploying solutions such as ML models, API and dashboards Deploying data science solutions on a cloud platform; Azure ML and MSFT Certificate are highly desirable MLOps is highly desirable, e.g. CI/CD, Feature Store, drift monitoring, MLflow, DVC, Docker, Kubernetes Software development experience is desirable Algorithm design experience is desirable Data architecture knowledge is desirable 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 ❯

of git Experienced in deploying solutions such as ML models, API and dashboards Deploying data science solutions on a cloud platform; Azure ML and MSFT Certificate are highly desirable MLOps is highly desirable, e.g. CI/CD, Feature Store, drift monitoring, MLflow, DVC, Docker, Kubernetes Software development experience is desirable Algorithm design experience is desirable Data architecture knowledge is desirable More ❯

Senior Data Scientist (Natural Language Processing) Total Remuneration: £57,879 to £68,146 Pay Supplement: The base salary for this role is £46,677 - £54,957 This job qualifies for Digital, Data and Technology Annual Pay supplement of 24% which More ❯

GlobalLogic are hiring for an MLOps engineer to work on cutting edge projects within our GenAI team. To be successful in the position we require experience in some/all of these areas: Proven experience as an MLOps Engineer or in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML … engineering concepts, including data pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ML systems. Skills with MLOps concepts and principles. Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization tools (e.g., Docker, Kubernetes). Proficiency in programming languages such as Python, experience with AI/… ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g., Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). #J-18808-Ljbffr More ❯

Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field Proficient in Python (core skill), with strong experience in SQL 5+ years of experience as MLOps engineer or DevOps roles, working with MLOps platforms Experience with Kubernetes on a major cloud provider and IAC **Please note that this role does not offer visa sponsorship** How to More ❯

the right tool doesn’t exist, we build one. We harness and channel the power of AI to create positive, meaningful change. About Fuzzy Labs Fuzzy Labs is an MLOps consultancy obsessed with the open-source ecosystem. We partner with data-science teams in the private and public sectors to get machine-learning products into production faster, safer, and with … open. We doubled revenue in the past 12 months and have equally bold growth plans for the year ahead. We’re creating an exciting new opportunity for a Junior MLOps Engineer. You’ll learn and grow alongside experienced engineers and technical leaders while immersing yourself in this cutting-edge area of technology. About the Role We’re based in central … tools, and best practices in a supportive environment. Alongside client work, you’ll also contribute to our R&D projects and have opportunities to develop your voice within the MLOps community through writing blogs, producing videos, and exploring new technologies. Who We’re Looking For You do not need an existing MLOps background—this role is ideal for recent graduates More ❯

production. We work closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline. The Role We are looking for a MLOps Engineering Manager to join our team and help shape the future of train travel. You will be part of a highly innovative AI and ML team working alongside engineers, scientists … have the opportunity to work with fellow ML enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users. As a MLOps Engineering Manager at Trainline you will... Build a new team of MLOps Engineers working alongside ML Engineers, Data Engineers, Software Engineers, Data Scientists and Product Managers Define MLOps processes and … modelling and evaluation techniques. Have experience with Cloud infrastructure (ideally AWS), DevOps technologies such as Docker or Terraform and CI/CD processes and tools. Have previously worked with MLOps tools like MLFlow and Airflow, or on common problems such as model and API monitoring, data drift and validation, autoscaling, access permissions... Have previously worked with monitoring tools such as More ❯

About the Role We are seeking a Senior MLOps Engineer to join our AI team and drive the design, deployment, and continuous improvement of our MLOps platform. In this role, you will have the autonomy to shape our infrastructure, ensuring scalable, efficient, and robust operations that support rapid model iteration and deployment at scale. Key Responsibilities: Design & Implement ML Workflows … Build and Scale Our MLOps Platform Design, develop, and optimise a high-throughput model inference system for production-grade AI. Create streamlined workflow pipelines for model training, testing, monitoring and deployment, leveraging cloud-native tools. Cloud & Container Management: Deploy and manage applications using AWS services, Kubernetes, Docker, and other DevOps best practices. LLM Deployment & Fine Tuning: Drive the deployment and … Collaborate Across Teams: Work closely with Machine Learning engineers to enable their delivery What We’re Looking For: Our ideal candidate will have a strong background in machine learning, MLOps, and cloud technologies with hands-on experience across the following areas: Cloud & DevOps Expertise: Experience with AWS, Kubernetes, and Docker. Proven skills in designing and managing CI/CD pipelines 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 with cross-functional teams to align AI … highly desirable. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, Scikit-learn. Experience deploying AI solutions using AWS, GCP, or Azure. Hands-on experience with MLOps, CI/CD, and model performance monitoring. Background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a plus. Passion for human-centred AI 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 ❯

Press Tab to Move to Skip to Content Link • Job Title: Senior MLOps/GenAI Infrastructure Engineer • Location: London/Salford/Glasgow/Newcastle/Cardiff (This is a hybrid role and the successful candidate will balance office working with home working) • Band: D • Salary: up to £59,600 - £69,800 (The expected salary range for this role reflects … modern digital ecosystem using exciting technologies and do the best work of their careers. Your Key Responsibilities And Impact Designing, developing, and maintaining tools that support data science and MLOps/LLMOps workflows. Collaborate with Data Scientists to deploy, serve, and monitor LLMs in real-time and batch environments using Amazon SageMaker, Bedrock Implement Infrastructure-as-Code with AWS CDK … and knowledge-sharing through comprehensive documentation, technical deep dives, brown bag sessions, internal workshops, and active mentorship of team members. Your Skills And Experience Extensive experience of DevOps/MLOps experience with a strong focus on building and delivering scalable infrastructure for ML and AI applications using Python and cloud native technologies Experience with cloud services, especially Amazon Web Services 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, or Azure. Hands-on experience with MLOps, CI/CD for ML, and model performance monitoring. Background in behavioural biometrics, human-computer interaction, or large-scale sensor/time-series data is a strong plus. A passion More ❯

attribution, predicting customer propensity, segmenting customer groups based on behavioral 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 … Excellent communication and problem-solving skills. Available 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 Benefits vary More ❯

use cases, and translate business needs into AI/ML solutions. Develop, test, and optimize AI models, ensuring they align with business goals and regulatory requirements. Work closely with MLOps engineers and the wider Tech and Data teams to deploy production-ready solutions. Stay ahead of industry trends, particularly in Data Science, NLP, and GenAi advancements, and share insights across … NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks for building end-to-end ML pipelines. Proven ability to lead and deliver data science projects in an agile environment. Excellent stakeholder management and communication skills to bridge the More ❯

R&D into emerging techniques (e.g., graph neural networks for inventory routing, GenAI for buyer personalisation). - Manage and mentor a Senior Data Scientist, fostering growth in model optimisation, MLOps, and stakeholder collaboration. - Coordinate with Data Engineering to ensure seamless data pipelines for model inputs (e.g., real-time inventory feeds, third-party economic data). 3. Cross-Functional Collaboration - Partner … 7+ years in Data Science, with 2+ years leading teams in B2B, automotive, fintech, or supply chain domains. - Expertise in production-grade ML (model deployment, A/B testing, MLOps) and tools like MLflow, Airflow, or Kubeflow. - Mastery of Python, SQL, and cloud platforms (AWS/Asure/GCP). - Proven track record solving business problems with ML (e.g., pricing More ❯

R&D into emerging techniques (e.g., graph neural networks for inventory routing, GenAI for buyer personalisation). - Manage and mentor a Senior Data Scientist, fostering growth in model optimisation, MLOps, and stakeholder collaboration. - Coordinate with Data Engineering to ensure seamless data pipelines for model inputs (e.g., real-time inventory feeds, third-party economic data). 3. Cross-Functional Collaboration - Partner … 7+ years in Data Science, with 2+ years leading teams in B2B, automotive, fintech, or supply chain domains. - Expertise in production-grade ML (model deployment, A/B testing, MLOps) and tools like MLflow, Airflow, or Kubeflow. - Mastery of Python, SQL, and cloud platforms (AWS/Asure/GCP). - Proven track record solving business problems with ML (e.g., pricing More ❯

advanced analytics techniques, machine learning approaches, and modern pricing tools. ML Engineering Integration: Partner with ML Engineering to elevate model sophistication, overseeing integration with Radar API and ensuring smooth MLOps deployment pipelines. Leadership & Mentoring: Support and mentor junior analysts, sharing knowledge and promoting best practices across the team. Who are you: We know we have high expectations, so please don … and deliver meaningful change end-to-end Excellent communication and stakeholder skills, with the ability to present technical insights clearly to non-technical audiences Nice-to-have Familiarity with MLOps and development best practice, including production-grade model design and deployment, version control (e.g. Git), code reviews, CI/CD pipelines, unit testing, and collaborative workflows such as Agile. Experience More ❯

in productionising machine learning modelsand/or real-time systems Have knowledge of DevOps technologies such as Docker and Terraform, building APIs, CI/CD processes and tools, and MLOps practices and platforms like MLFlow and monitoring Have experience with agile delivery methodologies Have good communication skills Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline … agent AI systems Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, TensorFlow, etc...) PySpark AWS cloud infrastructure: EMR, ECS, S3, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow, Jenkins More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, extra festive time More ❯

tailored solutions. Data Science Expertise: Apply diverse data science techniques across multiple industries and use cases, including machine learning, data visualization, natural language processing (NLP), application development (e.g. Shiny), MLOps, and generative AI (GenAI). Develop and deploy advanced data science models and algorithms to solve complex business problems. Mentor and guide junior data scientists, fostering a culture of continuous … leading and managing large customer engagements; Experienced in deploying workloads on Cloud infrastructure; Familiar with software development best practices; Extensive experience in machine learning, data visualisation, NLP, application development, MLOps, and GenAI; Strong strategic thinking and problem-solving skills; Excellent communication and presentation skills; Certifications: Azure Data Scientist Associate DP-100 (nice to have AI-102, DP-203, AZ More ❯