Senior ML Engineer: Remote AI, MLOps & Cloud

Williams Lea; United Kingdom; Hybrid; GBP 70,000 - 80,000; Full time

Benefits offered by this job

25 days holiday

Private Medical Insurance

Dental Insurance

Health Assessments

Cycle-to-work scheme

Retail vouchers

Job summary

Williams Lea seeks a highly skilled Senior ML Engineer to design, develop, deploy, and maintain scalable ML and Generative AI solutions for enterprise applications. The role covers end‑to‑end ML pipelines, LLM integrations, and production‑grade AI systems across AWS and Azure.

The successful candidate will have 6+ years' experience in Python, ML model deployment, and cloud‑native platforms, with a strong MLOps mindset and collaboration across data scientists, platform engineers, and product

Qualifications

• Bachelor’s or master’s degree in computer science or related field.
• Strong Python development and ML model deployment experience.
• Hands-on cloud experience with AWS and/or Azure.
• Experience with SageMaker/Bedrock/Azure ML or equivalents.
• Solid ML lifecycle, MLOps, CI/CD and monitoring knowledge.
• Experience with REST APIs and distributed systems.
• Familiarity with Docker, Kubernetes, Terraform.
• Experience with Generative AI, LLMs, LangChain or similar is a plus.

Responsibilities

• Design, build, and deploy scalable ML and Generative AI solutions in production environments.
• Develop end‑to‑end ML pipelines including data preprocessing, feature engineering, model training and monitoring.
• Integrate LLMs and AI services into enterprise applications and workflows.
• Work with cloud-native AI services including AWS SageMaker, Bedrock, Lambda, S3, CloudWatch, and Azure ML.
• Develop and optimize ML models using Scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, or Hugging Face.
• Implement MLOps best practices including CI/CD pipelines, model versioning, automated testing, monitoring, and governance.
• Collaborate with Data Scientists, Platform Engineers, Backend Teams, Product Owners, and Solution Architects.
• Support production releases, troubleshooting, model monitoring, and performance optimization.
• Ensure compliance with enterprise security, governance, and responsible AI standards.
• Contribute to AI architecture discussions, technical documentation, and solution design.

Skills

Python programming

ML model deployment

Cloud platforms AWS/Azure

SageMaker Bedrock Azure ML

ML lifecycle MLOps CI/CD

REST APIs

Docker Kubernetes Terraform

Generative AI / LLMs

Analytical / communication

Education

Bachelor’s or Master’s in CS/Data Science/AI

Tools

Docker

Kubernetes

Terraform

Job description

Williams Lea seeks a highly skilled Senior ML Engineer to design, develop, deploy, and maintain scalable ML and Generative AI solutions for enterprise applications. The role covers end‑to‑end ML pipelines, LLM integrations, and production‑grade AI systems across AWS and Azure.

The successful candidate will have 6+ years' experience in Python, ML model deployment, and cloud‑native platforms, with a strong MLOps mindset and collaboration across data scientists, platform engineers, and product