51 to 75 of 270 MLOps Jobs in England

track record of developing and deploying models at scale Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes) With preferred backgrounds covering some of the following: Experience with speech-to-text or text ...

observability, monitoring, alerting, incident response, and troubleshooting complex infrastructure, networking, security, and deployment issues. Desired Technical Skills Experience supporting machine learning workloads or MLOps practices in cloud environments. Experience with modern data lake, streaming, analytics, or cloud‐native BI architectures. Understanding of AWS cost optimisation and FinOps principles. Experience operating ...

track record of developing and deploying models at scale Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes) With preferred backgrounds covering some of the following: Experience with speech‐to‐text or text ...

experience in one or more object-oriented languages (e.g. Python, Go, Java, C++). Advanced SQL knowledge. Experience with modern ML engineering practices including MLOps, model lifecycle management, CI/CD, and monitoring. Knowledge of experimental design, analysis, and scientific methodology. Customer-centric and pragmatic mentality with a focus ...

Chambers & Partners is seeking a Senior DevOps Engineer to architect, scale, and secure our cloud infrastructure. You will drive IaC strategy, build robust GitOps practices, and own CI/CD pipelines in Azure DevOps, supporting ...

monitoring, deployment strategies, containerization) in a cloud environment, preferably AWS and Databricks. Strong understanding of the data science/ML research process, software engineering, MLOps, and DevOps best practices. Strong Python skills, including Pandas, NumPy, scikit‐learn; proficiency in SQL and NoSQL databases. Excellent communication, leadership, and stakeholder management skills. ...

associated architecture patterns Experience designing and managing APIs including REST and GraphQL Strong understanding of microservices and serverless architectures Practical experience with DevOps and MLOps practices including CI/CD pipelines Knowledge of security frameworks, identity management and authentication standards Desirable Skills for the AI Solutions Architect: Experience with enterprise ...

integrity policies are followed. Offer technical leadership in data engineering, artificial intelligence, and machine learning. Deploy auto AI using CI/CD together with MLOps greatest practices. While guaranteeing high availability and performance, make the best use of cloud assets. Lead groups in choosing technology agnostic data and artificial intelligence ...

prioritizing and executing tasks to meet timelines and deliver results. What you’ll bring 5+ years as an ML-focused software engineer, ML Engineer, MLOps Engineer, or similar, with hands-on production experience. Proven expertise with ML model deployment, API design, and integration into production environments. Strong Python programming ...

container orchestration (Kubernetes), service mesh, CI/CD, IaC, observability, and platform engineering Strong knowledge of real‐time streaming (Kafka/Pulsar), batch analytics, MLOps, model governance, and responsible AI patterns Security and resiliency expertise: zero trust, secrets management, identity, encryption, chaos engineering, disaster recovery, and site reliability practices Integration ...

Desirable: Exposure to machine learning frameworks such as PyTorch, JAX, Triton, TensorFlow Experience with distributed workload management systems such as Kubernetes, VLLM, Keras or MLOps pipelines Experience working with hardware simulators or emulators (e.g. QEMU). Experience developing for or working with FPGA-based systems. Experience with people management ...

LangChain/LlamaIndex-style tooling, multi-agent patterns) LLM evaluation, guardrails, and red-teaming tooling (hallucination detection, safety/bias testing) LLMOps/MLOps: model versioning, deployment pipelines, monitoring, and rollback for AI services in production Fine-tuning and parameter-efficient adaptation techniques where appropriate to use case Data engineering ...

Senior MLOps Engineer – AI Consultancy Manchester | £65k–£80k + Equity + Benefits We’re hiring a Senior MLOps Engineer to join a fast-growing AI consultancy based in Manchester City Centre (3 days on-site). You’ll take ownership of production ML systems and help shape how models … cloud platforms (AWS, Azure, or similar) Experience deploying systems you’ve helped design Excellent communication skills Eligible for SC clearance Nice to have Practical MLOps experience in live environments Kubernetes and IaC Experience with LLM or agent‐based systems Open source contributions or technical writing Perks £65k–£80k salary ...

with stakeholders and subject matter experts. Familiarity with high compute cloud‐based platforms and services, in particular AWS. Familiarity with code version control and MLOps deployment approaches. Required/Preferred Education and Licenses Advanced degree (MS or PhD) in Data Science, Computer Science, Biostatistics, or related field. 3 – 5 years ...

scalable applications. Experience making architecture and technology decisions within enterprise organisations. Strong knowledge of modern AI engineering practices, including LLMs, RAG, agentic workflows, and MLOps concepts. Experience working with cloud platforms, ideally AWS. Ability to balance innovation with risk, governance, and operational requirements. Strong stakeholder management and communication skills. Experience ...

level AI capability inside a large-scale AI adoption programme for a central government department. Where the Machine Learning Engineer trains models and the MLOps Engineer runs the platform, you sit closest to the end product: turning LLMs, retrieval systems, and agentic workflows into working, usable features that integrate with ...

Willingness to work on‐site in our Alkmaar office Nice to Have (But Not Required) Experience deploying ML models into production environments Familiarity with MLOps tooling such as MLflow, CI/CD workflows, and model monitoring Experience with AWS, Azure, or GCP Understanding of real‐time systems, motion synthesis ...

management of SHE and cGMP. Desirable Skills/Experience PhD or equivalent experience in a relevant scientific, engineering, or data field. Demonstrated experience operationalising MLOps, model lifecycle management, and validation in GxP contexts. Familiarity with generative AI, knowledge graphs, semantic layers, and digital twins for manufacturing and CMC. Experience leading ...

solutions with clarity, assurance and accountability at scale. To be successful as an AI Ops Platform Engineer, you should have experience with: LLMOps/MLOps at production scale, operating the full Generative AI lifecycle including models, prompts and agents, CI/CD pipelines, structured evaluation, drift and hallucination monitoring ...

management of SHE and cGMP. Desirable Skills/Experience PhD or equivalent experience in a relevant scientific, engineering, or data field. Demonstrated experience operationalizing MLOps, model lifecycle management, and validation in GxP contexts. Familiarity with generative AI, knowledge graphs, semantic layers, and digital twins for manufacturing and CMC. Experience leading ...

field Experience across a spectrum of libraries, frameworks and services : such as ML libraries e.g. TensorFlow or PyTorch model servers such as AWS Bedrock MLOps such as ML Flow or Sagemaker agent/AI orchestration such as LangGraph or MCP libraries Strong programming skills, especially in Python (other languages like ...

communication skills Experience contributing to and overseeing large-scale rollouts and infrastructure initiatives. Expertise in several of the following areas: robust python development, MLOps, containerization, cloud infrastructure (AWS and Azure), advanced search and recommendation technology, orchestration of ML pipelines for real-time inference, microservices architecture, model monitoring and governance. What ...

level of review and controls based on risk* Collaborate with Cloud, Data, Networks, and Digital teams to ensure secure configuration of AI infrastructure, including MLOps and compute environments* Guide programmes and product teams with clear, practical recommendations that balance security, delivery, and innovation* Drive compliance with regulatory, legal, and internal ...

Databricks is seeking a Senior Specialist Solutions Architect for AI/ML in London. You will be the trusted technical expert for ML/AI, guiding customers and the Field Engineering team to design production ...

Engineer and ML Engineer through to Senior, Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real … models at scale LLM and generative AI tooling exposure (LangChain, LlamaIndex, vector databases such as Pinecone, Weaviate or pgvector, RAG patterns, fine-tuning workflows) MLOps platforms (MLflow, Kubeflow, Vertex AI, SageMaker, Databricks or equivalent) Cloud experience (AWS, GCP, Azure), containerisation and basic data engineering/SQL Familiarity with experimentation ...