Senior Machine Learning Engineer - Remote Eligible

Senior Machine Learning Engineer

Williams Lea is the leading global provider of skilled, technology-enabled, business-critical support services, with long-term trusted relationships with blue-chip clients across investment banks, law firms and professional services firms. Williams Lea employees, nearly 7,000 people worldwide provide efficient business services at client sites in often complex and highly regulated environments, from centralised Williams Lea onshore facilities, and through best cost company offshore locations.

Purpose of the Role

As a Senior Machine Learning Engineer, you will play a central role in designing, developing, and scaling AI-powered solutions that address complex challenges in highly regulated industries such as legal and investment banking.

Working as part of a global engineering organisation — and reporting to the Lead ML Engineer — you will combine technical excellence, hands-on development, and team leadership. You'll help shape the Machine Learning Centre of Excellence, contributing to the direction of our engineering practice while mentoring junior engineers and collaborating across teams to deliver impactful solutions.

This role requires someone with real-world experience bringing ML/AI services to market at scale, strong communication skills, and the ability to collaborate with internal stakeholders, client teams, and partners — including AWS specialists.

If you're a curious, driven engineer with a passion for building smart, scalable AI solutions — and mentoring others while you do it — this is the role for you.

Key Responsibilities

Solution Design & Development

• Lead the design and implementation of scalable ML models and data pipelines to support AI-powered products in regulated domains
• Translate business challenges into technical ML solutions using the most appropriate algorithms, models, and tools
• Build, train, and evaluate models using Python (e.g. scikit-learn, pandas, NumPy) and frameworks like TensorFlow or PyTorch

Cloud-native ML Engineering

• Develop and deploy ML solutions on AWS, particularly using Amazon SageMaker
• Leverage AWS services (Lambda, S3, Redshift, CloudWatch) to build end-to-end solutions
• Own and improve CI/CD pipelines using Infrastructure as Code (Terraform, CloudFormation)

Collaboration & Thought Leadership

• Work closely with product teams, DevOps, data scientists, and external AWS partners to deliver reliable ML services
• Contribute to team-wide decision-making on architecture, toolsets, and process improvements
• Communicate ML concepts and solution rationale clearly to non-technical stakeholders and clients

Coaching & Mentoring

• Provide technical leadership to mid-level and junior ML engineers, including reviewing code, guiding experiments, and setting best practices
• Foster a culture of collaboration, curiosity, and continuous improvement
• Contribute to the growth of our global ML engineering team, including upskilling colleagues in India

Quality, Compliance & Documentation

• Ensure models and ML pipelines meet performance, accuracy, and compliance standards
• Maintain documentation for all stages of the ML lifecycle — from data pre-processing to deployment workflows
• Follow data security protocols and best practices in regulated environments

Required Experience & Skills

• 4–6 years of hands-on experience in machine learning engineering or data science roles
• Proven success in building and deploying AI/ML services at scale, ideally in regulated sectors (e.g. finance, legal, healthcare)
• Strong programming skills in Python and proficiency with libraries such as scikit-learn, pandas, NumPy, and at least one deep learning framework (e.g. TensorFlow, PyTorch)
• Deep understanding of ML algorithms, modelling techniques, and performance evaluation methods
• Hands-on experience with AWS cloud services, including SageMaker
• Experience with CI/CD practices, Docker, and Infrastructure-as-Code tools like Terraform or CloudFormation
• Solid understanding of MLOps principles and how to productionize ML systems in a scalable, maintainable way
• Experience leading small teams or mentoring engineers in a collaborative, agile environment

Preferred Qualifications

• Exposure to legal tech, contract analytics, or financial modelling using NLP, classification, or predictive models
• Experience working in cross-functional, geographically distributed teams
• Familiarity with MLOps tools like MLflow, Kubeflow, or Apache Spark
• Relevant certifications (e.g. AWS Certified Machine Learning – Specialty, TensorFlow Developer)

Key Traits for Success

• Strong problem-solving mindset and ability to break down complex challenges into practical, scalable ML solutions
• A creative engineer with a scientific approach — balancing experimentation with execution
• Naturally curious, self-motivated, and constantly looking to grow and help others do the same
• Comfortable working both autonomously and collaboratively
• Clear, confident communicator able to work across technical and non-technical teams

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 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.