1 to 25 of 99 Permanent MLOps Jobs in England

Strong knowledge of Machine Learning algorithms and statistics. Experience with SQL/NoSQL databases and big data tools (Spark, Hadoop preferred). Experience with MLOps tools such as Docker, Kubernetes, CI/CD pipelines. Preferred Skills Experience with LLMs/Generative AI (OpenAI, Hugging Face, LangChain). Cloud experience ...

Skills Experience with prompt engineering, fine-tuning LLMs, and building RAG-based solutions. Knowledge of financial instruments, pricing models, and risk analytics. Familiarity with MLOps and data governance in regulated environments. Why Apply? Work with major financial institutions on transformative AI projects. Exposure to the latest AI/GenAI technologies ...

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 ...

Take validated prototypes from our Data Science team and re-engineer them into high-performance, maintainable codebases that integrate seamlessly with client ecosystems. Infrastructure & MLOps: Build and maintain CI/CD pipelines specifically for machine learning, ensuring that deployments are predictable, reproducible, and secure. Performance Optimization: Profile and optimize model ...

serving, versioning, and lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Databricks Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly ...

Spark. • Ethics: Knowledge of AI ethics and governance. • Methodologies: Agile and Scrum project management. Desired Skills & Experience • Deep knowledge of machine learning operations (MLOps) and experience in deploying, monitoring, and maintaining AI models in production environments. • Proficiency in data engineering for AI, including data preprocessing, feature engineering, and pipeline creation. ...

every model we build is fair, free from bias, and explainable to consumers, customers, and regulators. Engineering & Deployment: Work within the engineering team on MLOps to containerise, deploy, and monitor models in high-scale production. Skills & Requirements Core Data Science: Foundational Stats: You must have an excellent grasp of Linear ...

production-ready systems. Academic Foundation Bachelors or Masters degree in Computer Science, Machine Learning, Engineering , or a closely related discipline. Bonus Points Experience with MLOps and model serving platforms such as BentoML, MLflow, or SageMaker . Hands-on work with streaming and batch data pipelines using tools like Spark, Airflow ...

cross-functional squad (DevOps, data engineers, developers, testers, Infosec) to productionise AI services in AWS. Enhance and innovate esure’s tech stack, including MLOps, CI/CD pipelines, UI, and our AI Python library. Assess third-party GenAI and LLM technologies to determine feasibility and cost–benefit. Skills and experience ...

technical challenges Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical discipline Bonus Skills/Experience Understanding of MLOps, model serving, scaling and monitoring workflows (e.g., BentoML, MLflow, Vertex AI, AWS Sagemaker) Experience building streaming + batch data ingestion and transformation pipelines (Spark/ ...

Azure) and containerisation (Docker, Kubernetes) Solid understanding of ML fundamentals (model training, evaluation, common architectures) Desired Skills (Bonus Points) Experience with MLOps tooling (MLflow, Kubeflow, Weights & Biases, or similar) Building data pipelines (real-time or batch) using tools like Apache Spark, Kafka, Airflow, or dbt Familiarity with recommender systems, transformers ...

TensorFlow, PyTorch, or scikit-learn Eagerness to learn, curiosity, and a problem-solving mindset Nice to Have Cloud experience (AWS, GCP, Azure) Familiarity with MLOps tools (Docker, MLflow, Kubeflow) Deep learning knowledge (CNNs, RNNs, Transformers) Internship, research, or academic projects in ML/AI Why Join Hands-on experience with ...

your skills in a fast-moving AI environment. Nice to Have (But Not Essential) Experience with vector databases , embeddings, or prompt optimisation. Exposure to MLOps , model deployment, or monitoring tools. Background in data engineering, front-end development, or UX-aware AI applications . Interest or experience in healthcare or regulated ...

Design and implement Onsera's agentic AI platform – architect LLM/agent framework selection, standardized patterns for tools, memory, guardrails, evaluation, and observability Define MLOps protocols for agentic systems – environment separation, versioning of prompts, tools, and policies, cost controls, rate-limiting, and fail-safe mechanisms Bridge data science and platform ...

Microsoft AI Foundry or Ollama advantageous). Strong grasp of CI/CD, testing, version control, secure coding, and modern engineering workflows. Exposure to MLOps tools such as MLflow, Kubeflow, or Azure ML. ...

cross-functional squad — DevOps, data engineers, developers, testers and Infosec — to productionise AI services in AWS. Build proficiency in esure’s tech stack, including MLOps, CI/CD pipelines, UI tools and our AI Python library. Develop prompts, fine-tune open-source base-models and track results. Skills and experience ...

cloud-native (GCP/Azure/AWS), Kubernetes, API-first integration, and observability stacks (metrics, logs, traces) Experience in ML/AI (feature engineering, MLOps, model monitoring), automation frameworks (RPA/BPM/runbooks), and security/compliance. Proven leadership in large-scale digital transformation, operating model change, vendor management ...

experience with ML frameworks (scikit‐learn, XGBoost, PyTorch, TensorFlow, LightGBM). Strong exposure to LLMs, prompt engineering, RAG, and evaluation frameworks. Familiarity with MLOps tooling: CI/CD, experiment tracking, model registries, monitoring, containers. Please note: This role cannot provide VISA sponsorship . ...

scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps practices, including deployment, monitoring, and retraining pipelines. Proven ability to work cross-functionally with marketing, CRM, product, and engineering teams. Excellent communication, leadership, and stakeholder ...

deep learning frameworks (TensorFlow, PyTorch) Solid understanding of ML algorithms, statistics, and data modelling Experience with large-scale data tools (Hadoop, Spark, Kafka) Cloud & MLOps experience (AWS, Azure, or GCP) NLP experience highly beneficial Strong leadership, communication, and stakeholder management ...

skills and experience with ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch). Experience with model deployment, monitoring and ML pipelines (e.g. CI/CD, MLOps concepts). A collaborative mindset with strong communication skills and experience working in cross-functional teams. If this role looks of interest, apply below. ...

junior team members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision, or time-series analysis Ability to design experiments and apply statistical validation Understanding of Responsible ...

drive best practice across secure software delivery, deployment automation, and live system operations. Working in the defence domain presents unique challenges across DevSecOps, MLOps and secure cloud adoption . You will use modern cloud and automation technologies to accelerate deployments while applying SRE principles to improve system resilience and uptime. ...

explain clearly to non-technical audiences DS background that has moved into AI engineering/LLM product delivery is ideal Bonus: Databricks, Azure, MLOps/CI-CD experience Interested? Please apply below. ...

data workflows 💬 Strong communication skills and a collaborative mindset ⭐ Big bonus points for: ❄️ Experience with Snowflake 🧱 Experience with Databricks ⚙️ Exposure to ML pipelines, MLOps, or production ML systems If you’re excited about building AI systems, learning fast, and growing your career in a supportive, high-impact environment ...