1 to 25 of 41 MLOps Jobs in the South East

environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What We Offer Fully remote working A 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 ❯

environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯

environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯

the ability to balance research innovation and commercial value delivery. Comfortable operating across cloud environments (GCP, Azure, AWS) and deploying AI/ML systems at scale. Strong knowledge of MLOps practices and infrastructure including CI/CD, model versioning, orchestration, and monitoring. A collaborative and inspiring leader who brings out the best in technical teams and communicates complex concepts to More ❯

and eagerness to stay ahead of the curve Desirable Skills Background in agile and collaborative project delivery Familiarity with data visualisation tools (e.g. Tableau) Exposure to model monitoring and MLOps practices MSc or equivalent in a quantitative discipline (e.g. Data Science, Statistics, Computer Science) *Rates depend on experience and client requirements More ❯

Physics, or related fields 4+ years Systems Engineering or related experience 2+ years experience with CV, NLP, and LLM architectures Knowledge of large-scale software architectural patterns Experience with MLOps, automation tools, containerization (Docker, Kubernetes), and ML lifecycle management Knowledge of Rust is a plus Experience with fine-tuning GenAI models and Reinforcement Learning is a plus Customer focus and More ❯

working in B2C, e-commerce, subscription, retail, or fintech industries is a strong advantage Nice to Have Experience with NLP for customer feedback or support ticket analysis Exposure to MLOps for model deployment and monitoring Familiarity with tools like Amplitude, Mixpanel, or Google Analytics Why Join Us? Shape data-driven strategy for how we understand and engage with our customers More ❯

CI/CD pipelines. Experience writing clean, efficient, and modular code suitable for production environments. Desirable Skills or Knowledge Familiarity with AMO physics or quantum machine learning. Experience with MLOps best practices. Knowledge of systems like Apache Kafka, MQTT or real-time data pipelines. Experience with cloud platforms (AWS, Azure, GCP). Deep expertise in time series modelling techniques (e.g. More ❯

or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯

or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯

project governance, lifecycle management, and ROI tracking. Vendor Management: Evaluate and manage relationships with external AI platform vendors and partners. Stay Ahead: Keep ClearCourse at the forefront of GenAI, MLOps, RPA, and regulatory trends. What You’ll Bring: Essential: Proven experience leading AI, ML, or automation initiatives in a digital or tech-driven organisation Strong knowledge of GenAI, NLP, LLMs More ❯

and AWS (serverless) Background in OCR, NLP, and scalable automation architectures Solid understanding of Agile, DevOps, and XP practices Comfortable with stakeholder engagement and cross-functional collaboration AWS Textract, MLOps, PyTorch Kubernetes, Docker, OpenShift Role Fully remote £550 Per Day outside IR35 6 month contract (2 year project) Starting end of July Please get in touch for further information. Morgan More ❯

ML systems, data pipelines, and CI/CD processes. Conduct security risk assessments and threat modelling on AI/ML workflows. Drive secure coding practices and integrate security into MLOps/DevOps pipelines. Address challenges such as adversarial attacks, data poisoning, and prompt injection. Define access control, authentication, and encryption standards across platforms. Work with data scientists and engineers to More ❯

you will design and develop scalable, cloud-based backend systems using multiple programming languages. You'll contribute to QA, automation, and infrastructure management while supporting DevOps and AI/MLOps practices. Collaboration on architecture, environment lifecycle, and regulatory compliance is key. As Full Stack Software Engineer, you will have to : Develop scalable software systems for back-end that will be More ❯

environments Strong technical background in data engineering, analytics, or science Experience working with Finance and Risk teams Familiar with AWS and modern data/AI stacks (SQL, Python, MLflow, MLOps) Strategic mindset with ability to scale teams and influence at C-level More ❯

Experience:* Python, including APIs, data structures, and async processing* Databricks/Microsoft Fabric* Cloud, preferably Azure (Data Lake, Functions, App Services)* Containerisation with Docker and CI/CD pipelines* MLOps tooling (MLFlow, Git-based versioning, environment tracking)Desirable Skills & Interests* LangChain, Langflow, or similar frameworks for building AI agents* LLMs or intelligent automation workflows* High-availability, scalable systems (microservices, event More ❯

in data engineering, analytics, or data science. Experience with modern data stacks (e.g., SQL, dbt, Airflow, Snowflake, Looker/Power BI) and AI/ML tooling (e.g., Python, MLflow, MLOps). A track record of building and managing high-performing data teams. Strategic thinking and ability to influence senior stakeholders, comfortable in dual-regulated environments. HOW TO APPLY: Please send More ❯

libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company Market leading More ❯

cloud-based data platforms, ETL pipelines, and distributed data processing frameworks. Experience in building and optimizing ML pipelines, including feature engineering, model training, deployment, and monitoring. Deep understanding of MLOps best practices, including CI/CD for ML, model versioning, experiment tracking, and reproducibility. Experience with tools used for statistical analysis, predictive modeling, and AI/ML development. Familiarity with More ❯

with large-scale data and cloud-based environments. Background in consulting or client-facing project delivery. Familiarity with sectors such as manufacturing, energy, healthcare, or public sector. Understanding of MLOps and data science solution lifecycle. Why Join? Work on groundbreaking AI projects with real-world applications.? Collaborate with a team that values innovation, creativity, and measurable impact.? Opportunity to influence More ❯

Senior ML & AI Backend Engineer - Big Data, LLMs & MLOps About the Role We're an ambitious, fast-moving tech company developing next-generation solutions at the intersection of advanced Machine Learning, Big Data, and Large Language Models (LLMs). We're looking for a hands-on Senior ML & AI Backend Engineer to design and build the robust backend systems that … for you. What You'll Do Architect and implement scalable backend systems powering ML models and LLMs in production. Design, build, and maintain end-to-end ML pipelines, championing MLOps best practices for deployment, monitoring, and iteration. Develop solutions for big data storage and processing, ensuring data quality, security, and efficiency. Integrate and optimize both classical ML models and LLMs … systems. About You You're fluent in Python and experienced with leading ML/AI frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face). You have a solid background in MLOps: experiment tracking, CI/CD for ML, model versioning, deployment, and monitoring. You've built scalable backend systems and APIs (RESTful/GraphQL), with solid experience in microservices and databases 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 ❯

tuning pipelines to adapt foundation LLMs to enterprise-specific datasets• Work with embedding models and OCI Vector Database to implement RAG Solutions.• Provide technical guidance and best practices around MLOps, model versioning, deployment automation, and AI governance.• Collaborate with functional SME’s, application teams, and business stakeholders to identify AI opportunities and design the right cloud and AI first solutions. More ❯

Proven ability to design and deploy full-stack AI pipelines in production Strong experience in backend engineering , ideally with Go and ML frameworks like PyTorch or TensorFlow Familiarity with MLOps , cloud infrastructure (AWS) , Kubernetes , and Terraform Experience evaluating and deploying models (including anomaly detection, RAG, and clustering) in noisy, evolving data environments Nice to Have: Experience with Perl Knowledge of More ❯