Senior ML Engineer

Senior ML Engineer

Salary: £70,000 - £80,000 dependant on experience per annum, plus company benefits

Location: Remote United Kingdom

Contract: Full Time

Shifts: 37.5 hours per week, Monday – Friday,9.00am until 5:30pm with 1 hours unpaid lunch break

Work model: Hybrid

Williams Lea seeks a Highly Skilled Senior ML Engineer to join our team!

Williams Lea is the leading global provider of tech-enabled business and marketing services helping clients manage and transform processes through resilient, scalable 24/7 operations. We combine deep expertise, agentic AI-imbedded workflows, and a global delivery model into a tech-enabled, seamless human expert-in-the-loop experience that helps clients achieve superior business outcomes.

Built on a strong heritage and great client relationships, we harness deep industry expertise, emerging technology and our global “Optishore™” delivery model to plan, build, execute and measure business processes, driving operational agility and digital transformation at speed and scale.

Williams Lea, an RRD company, serves clients in 20 countries across four continents and has 15,000 employees worldwide.

Purpose of role 

We are seeking a highly skilled Senior ML Engineer with a minimum of 6 years of experience to design, develop, deploy, and maintain scalable Machine Learning and Generative AI solutions for enterprise and client facing applications. The role involves working on end-to-end ML pipelines, LLM integrations, cloud-native AI platforms, and production grade AI systems across AWS and Azure environments. The ideal candidate should possess strong experience in Python development, ML model deployment, cloud technologies, MLOps practices, and production AI systems.

The recruitment process will involve an initial 45 minutes MS teams interview to understand suitable skills and experience, successful applicant will be invited to a 45 minutes technical assessment which will involve a deployment/coding followed by panel questions and answers.

Key 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, evaluation, deployment, 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 frameworks.
• 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 activities.
• Ensure compliance with enterprise security, governance, and responsible AI standards.
• Contribute to AI architecture discussions, technical documentation, and solution design.

Key Skills and Personal attributes

• Bachelor’s or master’s degree in computer science, Data Science, Artificial Intelligence, or related field.
• Strong proficiency in Python programming.
• Experience in Machine Learning model development and deployment.
• Hands-on experience with cloud platforms such as AWS and/or Azure.
• Experience with SageMaker, Bedrock, Azure ML, or equivalent ML platforms.
• Strong understanding of ML lifecycle, MLOps, CI/CD, and model monitoring.
• Experience with REST APIs, event-driven architectures, and distributed systems.
• Knowledge of Docker, Kubernetes, Terraform, or infrastructure automation tools is preferred.
• Experience with Generative AI, LLMs, LangChain, LangGraph, or RAG systems is an advantage.
• Strong analytical, problem-solving, and communication skills

Using AI in your application

We’re happy for you to use AI tools to research us, polish your cv/cover letter, and practice interviews. Please make sure everything you submit reflects your authentic skills and experience.

To keep things fair, please don’t use AI to invent or exaggerate achievements, complete assessments (unless we say it’s allowed), or to generate live interview answers.

Rewards and Benefits

We believe in supporting our employees in both their professional and personal lives. As part of our commitment to your well-being, we offer a comprehensive benefits package, including but not limited to:

• 25 days holiday, plus bank holidays(pro-rata for part time or fixed term roles)
• Salary sacrifice schemes, retail vouchers – including our TechScheme which can be used on a range of gadgets such as Smart TV’s, laptops and computers or household appliances.
• Life Assurance
• Private Medical Insurance
• Dental Insurance
• Health Assessments
• Cycle-to-work scheme
• Discounted gym memberships
• Referral Scheme

You will also have the opportunity to work for a global employer who is dedicated to offering each and every employee an enjoyable, challenging and rewarding career with future career development prospects!

Equality and Diversity

The Company values the differences that a diverse workforce brings to the organisation and will not discriminate because of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race (which includes colour, nationality and ethnic or national origins), religion or belief, sex or sexual orientation (each of these being a “protected characteristic” in discrimination law). It will not discriminate because of any other irrelevant factor and will build a culture that values openness, fairness and transparency.

If you have a disability and would prefer to apply in a different format or would like to make a reasonable adjustment to enable you to make an interview please contact us at careersatWL@williamslea.com(we do not accept applications to this email address).

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