1 to 25 of 38 MLOps Jobs in the South East

/GenAI strategies aligned with business objectives. Designing and developing NLP solutions using techniques such as text classification, NER, topic modeling, and text generation. Collaborating with data engineers and MLOps teams to ensure clean data pipelines and seamless model integration. Applying LLMs (e.g., GPT, BERT, LLaMA2) and knowledge graphs to enhance natural language understanding and reasoning. Conducting exploratory data analysis More ❯

scalable AI applications across the enterprise. Work with a multi-functional team (DevOps, data engineers, developers, testers, Infosec) to productionize AI services on AWS. Enhance our tech stack, including MLOps, CI/CD pipelines, UI, and AI Python libraries. Develop prompts, fine-tune models, and track results. Evaluate third-party GenAI and LLM technologies for cost-benefit analysis. Deliver projects More ❯

Engineering, Data Science, or related field. Experience with streaming data technologies (e.g., Kafka, Kinesis). Familiarity with data cataloging and metadata management tools. Exposure to machine learning pipelines or MLOps is a bonus. At bp, we provide the following environment and benefits to you: A company culture where we respect our diverse and unified teams, where we are proud of More ❯

Engineering, Data Science, or related field. Experience with streaming data technologies (e.g., Kafka, Kinesis). Familiarity with data cataloging and metadata management tools. Exposure to machine learning pipelines or MLOps is a bonus. At bp, we provide the following environment and benefits to you: A company culture where we respect our diverse and unified teams, where we are proud of More ❯

Engineering, Data Science, or related field. Experience with streaming data technologies (e.g., Kafka, Kinesis). Familiarity with data cataloging and metadata management tools. Exposure to machine learning pipelines or MLOps is a bonus. At bp, we provide the following environment and benefits to you: A company culture where we respect our diverse and unified teams, where we are proud of More ❯

programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. are a plus. Additional Information What’s in it for you?: Competitive salary that reflects More ❯

real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯

build, and deploy production-grade ML systems that have a direct impact on government services and policy delivery. What you'll be doing Designing and delivering software, infrastructure, and MLOps systems that bring ML models into real-world use. Collaborating in cross-functional teams with engineers, data scientists, product managers, and designers. Creating scalable, reusable tools that improve ML deployment More ❯

and transformer-based architectures. Strong Python skills and familiarity with key ML/DL libraries. Experience with Azure (or similar cloud platforms), containerization (Docker/Kubernetes a plus), and MLOps tools. Understanding of healthcare data privacy, compliance (e.g., ISO standards), and secure data handling. Strong communication skills and ability to work cross-functionally in a collaborative environment McGregor Boyall is More ❯

design, build, and operationalise production-grade AI systems that directly impact high-stakes projects in the UK. What you'll be doing Designing, building, and deploying software, infrastructure, and MLOps systems that leverage machine learning. Working in cross-functional teams with engineers, data scientists, product managers, and designers. Developing scalable, reusable tools that accelerate ML delivery. Providing technical expertise to More ❯

must be current) Strong experience in AI/ML engineering (Python, TensorFlow, PyTorch, etc.) Experience with cloud platforms (AWS, Azure, or GCP) Solid understanding of data pipelines, APIs, and MLOps Excellent problem-solving and communication skills More ❯

and incident management Hands-on experience enabling AI/ML in a data platform Strong ETL/ELT engineering skills Desirable Experience with Python and related tooling Understanding of MLOps practices (MLflow, Azure ML) Familiarity with real-time data technologies (Kafka, Delta Live Tables) If you're passionate about transforming the banking industry and eager to leverage your expertise to More ❯

and incident management Hands-on experience enabling AI/ML in a data platform Strong ETL/ELT engineering skills Desirable Experience with Python and related tooling Understanding of MLOps practices (MLflow, Azure ML) Familiarity with real-time data technologies (Kafka, Delta Live Tables) If you're passionate about transforming the banking industry and eager to leverage your expertise to More ❯

we’re looking for: Proven experience in AI/ML model development and deployment Strong skills with Python, TensorFlow/PyTorch, and cloud platforms (AWS/Azure/GCP) MLOps assurance and risk experinece Knowledge of data pipelines, model optimisation, and real-world deployments Details: Contract: 6 months (with view to extend) Location: London (Hybrid) Start: ASAP If you’re More ❯

on experience as a DevOps engineer with Google Cloud Platform. Proven expertise with AI/ML services on GCP, particularly Vertex AI, BigQuery ML, and TensorFlow. Solid understanding of MLOps principles, including building CI/CD pipelines for machine learning. Proficiency in Infrastructure as Code (IaC) using Terraform. Experience deploying and managing AI/ML workloads with Kubernetes/GKE. More ❯

on experience as a DevOps engineer with Google Cloud Platform. Proven expertise with AI/ML services on GCP, particularly Vertex AI, BigQuery ML, and TensorFlow. Solid understanding of MLOps principles, including building CI/CD pipelines for machine learning. Proficiency in Infrastructure as Code (IaC) using Terraform. Experience deploying and managing AI/ML workloads with Kubernetes/GKE. More ❯

Build and scale pricing models to drive revenue and customer value Lead experimentation (A/B, MAB, causal inference) and analytics projects Set best practices in data science and MLOps Mentor and manage a UK/US-based team Communicate insights and partner with product, engineering, and commercial teams What We're Looking For 10+ years in data science; 5+ More ❯

Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design and implement MLOps solutions covering many different technologies. Desirable Skills Background in DevOps with exposure to CI systems, e.g. Jenkins Familiarity with infrastructure as code, e.g. Ansible Experience, aptitude, and a desire to More ❯

ML architecture and system design (minimum 2 years) with proven expertise in hands-on coding AI solutions. Deep knowledge of machine learning frameworks, cloud platforms (AWS, Azure, GCP), and MLOps(machine learning operations) practices. Deep knowledge about design and implementation of secure integrations between AI solutions and legacy enterprise software, whilst ensuring compliance with government-level security requirements, implementing single More ❯

seek an adept expert to contribute significantly to our R&D team, bridging machine learning engineering with applied data science. You'll improve and manage our Machine Learning Operations (MLOps) on Azure, and participate in creating, assessing, and advancing various machine learning models and AI systems. Collaborate extensively with scientific and operational teams to guarantee the robustness, scalability, and reliability … informed decision-making and boost innovation. Help our CDMO's mission by turning research insights into practical solutions efficiently. Key responsibilities: Compose, construct, and uphold resilient machine learning operations (MLOps) pipelines that facilitate the complete lifecycle of AI modelsfrom creation to implementation and supervision. Guarantee the successful deployment of machine learning and large language models (LLMs) in practical operational settings … interpret, share, and act on. Key requirements: MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience. Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine More ❯

maintain secure AWS cloud infrastructure Implement and manage CI/CD and DevOps pipelines Champion data quality, security, and best practices Collaborate with cross-functional teams Implement and manage MLOps capabilities Essential Skills: Advanced Python programming skills Expertise in data engineering tools and frameworks (Apache Flink) Hands-on AWS experience (Serverless, CloudFormation, CDK) Strong understanding of containerization, CI/CD More ❯

reinforcement learning Model selection, training, validation, and evaluation Deep learning architectures (CNNs, RNNs, Transformers) Data Science Statistical analysis, feature engineering, A/B testing Experiment design and hypothesis testing MLOps & Engineering Scalable ML systems (batch and real-time) ML pipelines, CI/CD, monitoring, deployment Familiarity with tools like MLflow, Kubeflow, Airflow, Docker, Kubernetes Strategic skills Align ML initiatives with More ❯

ML architecture and system design (minimum 2 years) with proven expertise in hands-on coding AI solutions Deep knowledge of machine learning frameworks, cloud platforms (AWS, Azure, GCP), and MLOps(machine learning operations) practices. Deep knowledge about costing of AI models to produce reasonable ROI and modular reusable services with moderate level of maintenance Understanding of data architecture, API design More ❯

deploying AI applications using Azure AI tools. Hands-on experience with databases such as Cosmos DB and SQL Server. Knowledge of Azure cloud services and deployment pipelines (DevOps/MLOps). Strong coding skills in Python and experience with REST APIs. Experience ensuring compliance with data protection, cybersecurity, and ethical AI standards Desirable Qualifications: Microsoft Azure AI Engineer Associate or More ❯

and scaling cross-functional teams (Data Science, ML Engineering, Software Engineering, Managers). Defining the ML/AI roadmap and aligning it to business outcomes. Driving best practice in MLOps, deployment, observability, and automation. Working with cutting-edge approaches: deep learning frameworks, foundation models, knowledge graphs, etc. Being the voice of ML/AI leadership, setting standards, mentoring, and building More ❯