101 to 125 of 697 MLOps Jobs in England

Computer Science, Data Science, Machine Learning, or related field. Proven experience building and deploying AI applications in large-scale production environments. Experience with MLOps practices and tools for managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding ...

Computer Science, Data Science, Machine Learning, or related field. Proven experience building and deploying AI applications in large-scale production environments. Experience with MLOps practices and tools for managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding ...

across financial services, healthcare, manufacturing, retail, public sector, or other enterprise industries. Cloud & Infrastructure: Hands‐on experience with cloud architecture, Infrastructure‐as‐Code, DevOps, MLOps, or enterprise platform engineering. Pre‐sales & Customer Success: Experience supporting enterprise sales cycles, solution demonstrations, technical workshops, or proof‐of‐concept engagements. Enterprise Integrations: Experience ...

Engineering (Specialist Team)The impact you will have:Lead the architectural design of production-grade ML workloads on our unified platform, encompassing the entire MLOps lifecycle from end-to-end pipeline creation and optimization (training/inference) to seamless integration with cloud-native services.Provide advanced technical support to the Solution ...

maintain real-time AI pipelines using WebSockets and SSE , ensuring seamless low-latency delivery for voice (ASR/TTS) and text applications. Architecture & MLOps: Deploy and orchestrate models within containerized microservice architectures ( Docker/Kubernetes ), ensuring robust monitoring, security, and scalability. Collaborative Delivery: Work closely with Business Analysts and internal ...

Deep knowledge of LLM APIs, prompt engineering, and conversational AI patterns. Experience in fine‐tuning LLMs for domain‐specific enterprise applications. Strong expertise in MLOps and LLMOps, ensuring scalable, reliable, and monitorable model deployments. Experience with agentic frameworks and autonomous agent architectures. Proficiency in Python and modern software development practices ...

Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps & MLOps Customize and apply Deep Learningand Gen AI models for various use cases based on the business needs, data availability,systemand infrastructure requirements - including edge device ...

technical stakeholders. Desirable Experience The following would be advantageous: Multimodal AI and reasoning. Edge or offline AI deployments. Kubernetes, particularly EKS or OpenShift. MLOps, including model evaluation, monitoring and reproducibility. Observability for agentic AI systems, including model performance, agent behaviour and drift. Agent orchestration and inter-agent communication protocols such ...

with measurable impact, including deploying or working alongside ML/AI systems in production Bonus: Trust & Safety, Content Moderation, or Integrity engineering experience MLOps experience: deployment, monitoring, and versioning of ML models Experience with SQL, data analysis tools, real-time streaming systems (Kafka, Redis), or event-driven architectures Familiarity with ...

Generative AI.Demonstrated ability to architect end-to-end Data & AI solutions, with specific expertise in modern Generative AI concepts (e.g., fine-tuning, RAG, MLOps for LLMs), using either open source and/or ISV tools such as Dataiku, Domino, DataRobot etc.Strong proficiency in a core programming language (e.g., Python ...

data science solutions. Ensure sharing best practices and learnings with other squad members. Design and spearhead the development of Gen AI, AI Agents and MLOps platforms, applications, and solutions driven by GenAI, deep learning and machine learning to address business challenges and elevate product performance. Build standards and recommendations ...

datasets, and digging into why something failed.You've invested deliberately in your software engineering craft: testing, error handling, CI/CD, observability, and the MLOps practices that keep things healthy once they're live.You're hands-on across the GenAI stack: LLM APIs, retrieval and vector stores, agents with tool ...

digging into why something failed. You've invested deliberately in your software engineering craft: testing, error handling, CI/CD, observability, and the MLOps practices that keep things healthy once they're live. You're hands-on across the GenAI stack: LLM APIs, retrieval and vector stores, agents with tool ...

technical stakeholders. Desirable Experience The following would be advantageous: Multimodal AI and reasoning. Edge or offline AI deployments. Kubernetes, particularly EKS or OpenShift. MLOps, including model evaluation, monitoring and reproducibility. Observability for agentic AI systems, including model performance, agent behaviour and drift. Agent orchestration and inter-agent communication protocols such ...

science tooling, including: Version control (Git) Cloud platforms (AWS, GCP, or Azure) Experiment tracking and model management Workflow orchestration and containerisation Strong understanding of MLOps principles, including model monitoring, retraining, and lifecycle management. Proven ability to translate business problems into data science solutions that deliver measurable outcomes. Beneficial Exposure ...

comfortable documenting and defending architectural decisions and engaging in thoughtful technical debate.Not required, but it’s a plus if you also have:· Experience with MLOps/LLMOps frameworks and best practices· A PhD in Computer Science, Electrical Engineering or a related field.· A background or work experience in life-sciences ...

machine learning, and generative AI technologies to deliver innovative business solutions. Continuously improve platform performance, scalability, and operational efficiency while supporting AI governance and MLOps best practices. Unfortunately we are unable to progress with candidates that require sponsorship at this time Skills we would love you to have Experience working ...

modern generative models or agentic development approaches can enhance data processing and analytics solutions.Contribute to the adoption of advanced analytics and AI capabilities, including MLOps and AIOps.Data Management, Security & GovernanceEnsure data security and compliance with relevant standards and regulations, particularly in public sector and regulated environments.Implement robust data management ...

machine learning, and generative AI technologies to deliver innovative business solutions.Continuously improve platform performance, scalability, and operational efficiency while supporting AI governance and MLOps best practices.Skills we would love you to have Experience working with Snowflake, including SQL development, data modelling, orchestration, and integration management.Experience with Azure services, including Azure ...

Multimodal Pipelines - Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML Frameworks - Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms like Google Vertex AI or AWS Sagemaker. Education - BS in Computer Science, Engineering, Data Science, or equivalent technical field ...

anomaly detection.Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions.SQL and large-scale data analysis.Cloud-based data science platforms and MLOps practices.Data visualisation and storytelling tools.Desirable SkillsExperience within financial services, regulated environments or market infrastructure.Familiarity with Azure AI services and Microsoft AI ecosystem.Experience with observability ...

their AI/ML services.Proficiency in data manipulation and analysis using SQL and big data technologies (e.g., Spark, Hadoop) is a plus.Experience with MLOps tools and best practices for model deployment, monitoring, and governance.Education and Experience:Bachelor's or Master's, or equivalent degree in Computer Science, Data Science, Statistics ...

habit of fixing the class of problem rather than the instance. AI and ML operations: Experience operating model serving, LLM inference or MLOps pipelines in production is a strong plus. Familiarity with model APIs, vector databases, MCP or orchestration frameworks helps. Networking and security: VPC design, service mesh and zero ...

habit of fixing the class of problem rather than the instance. AI and ML operations: Experience operating model serving, LLM inference or MLOps pipelines in production is a strong plus. Familiarity with model APIs, vector databases, MCP or orchestration frameworks helps. Networking and security: VPC design, service mesh and zero ...

habit of fixing the class of problem rather than the instance. AI and ML operations: Experience operating model serving, LLM inference or MLOps pipelines in production is a strong plus. Familiarity with model APIs, vector databases, MCP or orchestration frameworks helps. Networking and security: VPC design, service mesh and zero ...