20 of 20 MLOps Jobs in the South East

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 ...

TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment, and monitoring • Experience working with cloud platforms such as AWS, GCP, or Azure • Strong analytical thinking and problem-solving skills Experience Required ...

ontologies (e.g., PyTorch, JAX, Spark, HL7, FHIR) (desirable) Familiarity with cloud infrastructure (Azure/AWS), infrastructure as code, Kubernetes, Linux, Docker, data pipelines, and MLOps tools (desirable) Passion for biomedical topics and startup experience (desirable) What’s on offer Competitive salary, bonus scheme, and strong benefits package Pension, enhanced sick ...

product-focused mindset, balancing experimentation with real-world value. Useful additional experience includes: AWS or GCP environments (SageMaker, Bedrock, Lambda, S3, Redshift). MLOps practices (monitoring, deployment, optimisation). Working with streaming data, transformer models or recommendation systems. What They Offer £70,000 to £90,000 salary. Hybrid working with ...

resolve incidents efficiently. Continuously improve ML Ops processes, tooling, and automation for efficiency and reliability. What Were Looking For Essential: 5+ years experience in MLOps, DevOps, or related roles. Strong knowledge of ML lifecycle management, deployment, monitoring, and model maintenance. Hands-on experience with Python (and ML frameworks), containerisation (Docker ...

experience in training and deploying computer vision models into production · Proven track record with LLM fine-tuning, prompt engineering and productionisation · Deep experience in MLOps on Azure, including CI/CD, monitoring and scaling pipelines. · Strong coding skills in Python, with frameworks such as PyTorch, FastAPI and Azure CLI. ...

working in cloud environments, ideally Azure. Solid understanding of software engineering fundamentals including APIs, distributed systems and secure system design. Experience with DevOps or MLOps practices such as CI CD, containerisation and monitoring. The confidence and gravitas to influence technical direction and guide a less mature AI function. A practical ...

Preferred Experience with multimodal reasoning Experience with edge or offline AI deployments Familiarity with Kubernetes (EKS/OpenShift) for monitoring and managing deployed applications MLOps experience - model evaluation, monitoring, reproducibility Observability tooling for agentic systems (model drift, agent behaviour, performance monitoring) Experience with agent orchestration patterns and inter-agent communication ...

traditional ML solutions end-to-end Comfortable in startup or scale-up environments — fast-moving, iterative, delivery-focused Strong Python engineering experience Experience with MLOps, CI/CD, IaC, and productionising ML models Ability to work collaboratively with product, data, and engineering teams Contract Details Location: Hybrid London ...

iteration. Hands-on experience scaling a modern cloud data platform (lake/warehouse, orchestration, streaming). Deep understanding of the full ML lifecycle and MLOps/analytics engineering best practices. Experience implementing data architecture standards, data contracts, and governance across domains. Leadership experience managing managers and senior ICs within growing ...

practices across their ML and data setup, ensuring it is ready to support multiple enterprise deployments. Key responsibilities: * Audit current ML architecture, pipelines, and MLOps practices * Identify gaps in documentation, reproducibility, and scalability * Introduce clear structure across model development, versioning, and deployment * Improve training and retraining workflows * Strengthen model monitoring … Python and hands-on ML engineering experience * Proven experience in productionising ML systems end-to-end * Experience auditing and improving existing ML setups * Strong MLOps experience (model versioning, monitoring, CI/CD) * Experience working with data pipelines (ETL/ELT, Spark or similar) * Comfortable working with messy, real-world data ...

develop intelligent systems and tools Collaborating with cross-functional teams to integrate AI into production environments Conducting research, experimentation, and rapid prototyping Implementing MLOps best practices (CI/CD, monitoring, retraining pipelines) Translating business and stakeholder needs into scalable technical solutions Continuously improving AI/ML systems, frameworks, and performance … Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker, CI/CD, and version control ...

develop intelligent systems and tools Collaborating with cross-functional teams to integrate AI into production environments Conducting research, experimentation, and rapid prototyping Implementing MLOps best practices (CI/CD, monitoring, retraining pipelines) Translating business and stakeholder needs into scalable technical solutions Continuously improving AI/ML systems, frameworks, and performance … Experience building ML models using frameworks like PyTorch, TensorFlow, or scikit-learn Hands-on experience with LLMs (prompting, RAG, fine-tuning, agents) Understanding of MLOps principles and tools (e.g. MLflow, DVC, Weights & Biases) Experience deploying solutions in AWS or cloud environments Familiarity with Docker, CI/CD, and version control ...

120k – 150k GenAI/Agentic AI – Brighton (Hybrid) – AI-native Scale-up GenAI | Agentic AI | Machine Learning | Python | PyTorch | AI Strategy | LLMs | RAG | MLOps | Leadership |Do you want to lead AI at the core of a truly AI-native business building the next generation of virtual sales assistants A company … balancing tech investment with customer value The credibility to lead technically and influence at exec level Desirable but not essential: Strong AWS, containerisation and MLOps knowledge Confidence engaging directly with customers and enterprise stakeholders Hybrid role - minimum once per week onsite in Brighton.If you want to sit at the heart ...

models Work as part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build and maintain robust MLOps pipelines to support scalable, reproducible, and automated model development, deployment, and monitoring Leverage tools such as Airflow for workflow orchestration and MLflow for experiment tracking … skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for gaining insight into real-world datasets and clearly communicating through data visualization ...

preprocessing, augmentation, and validation workflows. Run structured experiments, evaluate model performance, and iterate based on measurable results Build, deploy, and operate end-to-end MLOps pipelines, including experiment tracking, model versioning, and production monitoring. Package and deploy models using Docker and cloud infrastructure, with a focus on reliability and scalability … familiarity with the Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience ...

dependencies to support executive decision-making. * Provide technical guidance across the AI landscape including generative AI, agentic systems, retrieval-augmented generation, fine-tuning, MLOps, and on-premise/cloud-native ML platforms, ensuring recommendations are grounded in implementation reality. * Collaborate with the client's internal teams (programme management, data engineering … complex, regulated, or high-security environments. * Deep technical fluency across modern AI/ML stacks: on-premise and cloud platforms (AWS, Azure, GCP), MLOps tooling, LLM orchestration frameworks, data engineering pipelines, and AI governance. * Exceptional ability to translate technical complexity into strategic narratives for non-technical senior stakeholders. * Strong commercial ...

transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring. Design, architect, and operate low-latency, highly reliable cloud … strong hands-on use of ML/DL frameworks (e.g., PyTorch, TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure-as-code practices. Proven technical leadership experience including ...

needed for this role: Expert AI/ML Skills – Strong in both traditional ML and modern LLM/RAG/agentic workflows Production Deployment & MLOps – Comfortable shipping scalable AI systems using APIs, microservices, Docker/Kubernetes, and cloud (GCP ideal) Business Partnering – Able to translate business needs into clear technical … LlamaIndex, etc.) Proven track record of deploying AI applications into production environments Strong understanding of API development, microservices, and containerization (Docker, Kubernetes) Knowledge of MLOps best practices Excellent problem-solving skills and ability to work in a fast-paced environment So, what’s in it for you? Bonus Schemes ...

Machine Learning Engineer - £110k – £130k – Geospatial Tech 4 GoodMachine Learning | Deep Learning | Time Series | Climate | Remote Sensing | PyTorch | scikit-learn | Geospatial | AWS | MLOps | Python | Risk Modelling | FinTech |Do you want to work with a business building AI-native data system that bring clarity and credibility to nature-based assets … great for FinTech/quant backgrounds)• Climate/weather datasets (CMIP, forecast data)• Geospatial tools: rasterio, xarray, geopandas, GDAL• Remote sensing (optical, radar, LiDAR)• MLOps: CI/CD, containerisation, monitoring• Startup or fast-paced product environmentThe role offers £110k–£130k, a global team environment, and the chance to shape ...