51 to 75 of 93 MLOps Jobs in London

deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks) click apply for full job details ...

Azure OpenAI, Prompt Engineering, Cognitive Search, Form Recognizer. Data/Coding: Expert-level Python, PySpark, and Vector DB integration. Ops: Practical knowledge of MLOps and LLMOps lifecycles. Security: Must hold active UK Government SC Clearance. Certifications Mandatory: AZ-204 (Azure Developer Associate). Preferred: AZ-305 (Solutions Architect ...

Azure OpenAI, Prompt Engineering, Cognitive Search, Form Recognizer. Data/Coding: Expert-level Python, PySpark, and Vector DB integration. Ops: Practical knowledge of MLOps and LLMOps lifecycles. Security: Must hold active UK Government SC Clearance. Certifications Mandatory: AZ-204 (Azure Developer Associate). Preferred: AZ-305 (Solutions Architect ...

e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools.Be able to design and implement MLOps solutions covering many different technologies.Desirable SkillsBackground in DevOps with exposure to CI systems, e.g. JenkinsFamiliarity with infrastructure as code, e.g. AnsibleExperience, aptitude, and a desire ...

optimisation). Experience leading or managing data scientists on impactful ML/optimisation projects. Excellent Python and SQL skills, with clean, maintainable code. Practical MLOps experience (deployment, monitoring, lifecycle management) in a cloud environment (AWS or similar). Comfortable working with large, imperfect datasets and making sound, pragmatic decisions. Familiarity ...

. Practical experience with LLMs, RAG architectures, embeddings and transformers. Experience deploying models using cloud infrastructure and working with microservices or APIs. Familiarity with MLOps concepts such as monitoring, evaluation and continuous improvement. Strong communication skills and the ability to translate business problems into AI-driven solutions. A collaborative mindset ...

. Practical experience with LLMs, RAG architectures, embeddings and transformers. Experience deploying models using cloud infrastructure and working with microservices or APIs. Familiarity with MLOps concepts such as monitoring, evaluation and continuous improvement. Strong communication skills and the ability to translate business problems into AI-driven solutions. A collaborative mindset ...

Nice to Have Experience in high-growth or early-stage biotech/pharma Familiarity with GxP, HIPAA, or similar frameworks Exposure to data platforms, MLOps, or AI/ML infrastructure in R&D contexts Ownership of SOC 2 or similar certifications Benefits Committed to Care Healthcare, pension/ ...

learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall, F1, Intersection over Union, and others. Additional beneficial ...

MLOps Engineer Location: London, UK (Hybrid - 2 days per week in office) Day Rate: Market rate (Inside IR35 Duration: 6 months Role Overview As an MLOps Engineer, you will support machine learning products from inception, working across the full data ecosystem. This includes developing application-specific data pipelines, building ...

Operations, Digital, Risk). Knowledge of AI governance, risk, compliance, and responsible AI frameworks relevant to FS environments. Exposure to AI delivery teams, including MLOps, data engineering, AI consulting, or agent-development teams. Ability to translate complex technical capability into clear commercial value propositions. Comfortable assessing AI maturity, operating models ...

GDPR/DPA 2018); hands-on with platforms such as Microsoft Purview, Azure ML, Databricks, Power BI, Collibra, or Alation; exposure to MLOps practices. ...

deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities * End-to-end development of AI/ML solutions. * MLOps practices: CI/CD, model monitoring, retraining. * Use of open-source and enterprise tools (LangChain, Azure OpenAI, Databricks). * Generative AI features: embeddings, RAG, AI agents. …/ML delivery. * Legal/professional services experience is a plus. * AI/ML frameworks: PyTorch, TensorFlow, LangChain. * Cloud: Azure (preferred), AWS, GCP. * MLOps: CI/CD, model lifecycle, monitoring. * Generative AI: LLMs, RAG, chat agents. * Data engineering alignment: ETL, governance. * Strong coding, communication, and collaboration skills. * Strategic thinking, problem ...

Java and PythonExperience leading teams within SaaS, scale-up or high-growth environmentsSolid understanding of agile delivery and stakeholder managementExposure to AI, automation, MLOps or agentic AI approachesComfortable working flexibly to support international customersBenefits:Salary dependent on experienceOpportunity to shape engineering strategy within a growing AI-focused businessHands-on leadership ...

from the Ultralytics export toolkit . Knowledge of cloud AI services and training infrastructure across AWS, Google Cloud, and Azure, including GPU clusters and MLOps considerations. Proven ability to lead benchmarking, technical validation, and co-development programs using our benchmark capabilities and integration best practices. Strong ability to connect technical ...

experimental models into production-ready solutions, collaborating with engineers on deployment, monitoring, and optimisation. Build and maintain ML pipelines using AWS services and modern MLOps/LLMOps tooling. Implement robust versioning, experiment tracking, and reproducibility practices. Mentor junior engineers and contribute to team-wide AI knowledge sharing. Communicate complex technical … level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record transitioning models from experimentation to production with governance and quality controls. Experience developing ...

Senior ML Engineer will own the journey from experimentation and hypothesis testing through to secure, production-grade deployment, using a modern AWS-based MLOps and LLMOps platform. The Role The successful candidate will balance rapid experimentation with production readiness, prototyping and validating machine learning and generative AI approaches while ensuring …/B testing and statistical evaluation Proven experience moving models from experimentation into production with appropriate governance and quality controls Hands-on experience with MLOps tooling such as MLflow, Weights & Biases or Data Version Control Practical experience building LLM/GenAI applications, including prompt engineering and retrieval-augmented generation ...

client is looking for a MLOps Engineer and Tech Lead to join their team on a six month initial contract, working two days a week onsite in London and rest remotely. This role is Inside IR35. Essential skills/knowledge/experience: * Knowledge of machine learning frameworks (eg, PySpark, PyTorch ...

Senior Data Scientist - Recommender Systems Experience Salaries in the region of £65,000 - £75,000 DoE Hybrid working - 2 days central London office Job Reference J13031 Full UK working rights required/no sponsorship available ...

simulation + tele‐op logs, version them, apply weak‐supervision labelling, curate balanced datasets, and auto‐surface fresh failure cases into retraining. Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‐time edge inference. We’re Looking For: 3+ years building deep‐learning systems ...

Role - Senior Lead Analyst- Data Scientist Technology – Data science, MLops, GenAI Location – London, UK Job Description Today, the corporate landscape is dynamic, and the world ahead is full of possibilities! None of the amazing things we do at Infosys would be possible without an equally amazing culture, the environment where … leadership roles with team management. •Strong expertise in Azure Machine Learning, Python, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. •Design and implement ML pipelines on Azure Machine ...

Build out a robust GenAI application technology stack, from experimentation through to production. Develop, maintain and improve existing ML pipelines, data transformation workflows and MLOps practices. Create serverless data/ML pipelines in cloud environments (Azure preferred). Work closely with architects, senior developers, product owners and business analysts … building data transformation pipelines using SQL and NoSQL databases. Hands-on ownership of CI/CD (Jenkins/Azure DevOps/GitHub Actions) and MLOps in Azure ML/Azure AI Foundry/SageMaker/Vertex AI. Working knowledge of Infrastructure as Code (Bicep, ARM, Terraform). A test-driven ...

does for its clients. Often involves the following engineering disciplines : Cloud Engineering Data Engineering (not building pipelines but designing and building the framework) DevOps MLOps/LLMOps Often work with the following technologies : Azure, AWS, GCP Airflow, dbt, Databricks, Snowflake, etc. GitHub, Azure DevOps and related developer tooling …/CD platforms, Terraform or other Infra-as-Code MLflow, AzureML or similar for MLOps; LangSmith, Langfuse and similar for LLMOps The difference to our "AI Engineer" role is: Do you "use/consume" these technologies, or are you the one that "provides" them to the rest of the organization. ...

create real commercial leverage Skills and Experience Proven leadership in defining and delivering enterprise AI strategy, including GenAI Strong understanding of AI platforms, MLOps, and modern AI tooling (without needing to be hands-on) Experience translating AI opportunities into commercially impactful use cases at scale Exceptional communication, influence, and stakeholder ...

with sensor selection, placement, and calibration. Expertise in training and fine-tuning models for perception in novel or domain-shifted environments; Solid foundation in MLOps, including dataset management, training infrastructure, and deployment pipelines. Nice to have: Experience in construction robotics, heavy machinery, or large-scale manipulation tasks. Familiarity with vision ...