Machine Learning Engineer

Williams Lea Group Limited; United Kingdom; Remote; GBP 55,000 - 65,000; Full time

Job summary

A global provider of business-critical services is seeking a Machine Learning Engineer to contribute to AI-driven solutions. The role involves designing, coding, and deploying ML systems in a remote work environment. Candidates should have hands-on experience with Python and AWS, and a solid understanding of machine learning principles. This position offers a salary of up to £65,000 per annum and various benefits.

Benefits

25 days holiday plus bank holidays

Private Medical Insurance

Discounted gym memberships

Qualifications

• 2-5 years of experience in machine learning or AI engineering.
• Basic understanding of ML concepts and evaluation techniques.
• Experience in building and deploying ML systems.

Responsibilities

• Design and deploy ML models under senior engineers' guidance.
• Implement ML solutions on AWS and build CI/CD pipelines.
• Write clean, efficient Python code for ML algorithms.

Skills

Proficiency in Python

Analytical thinking

Problem-solving aptitude

Clear communication skills

Education

Bachelor's degree in Computer Science or related field

Tools

AWS (SageMaker)

Git

Docker

Job description

Machine Learning Engineer
Salary: Up to £65,000 per annum depending on experience, plus company benefits
Contract: Full time, permanent
Shifts: 37.5 hours per week Mon-Fri, 8:30am-5pm with a 1-hour unpaid break
Work model: Fully remote

Williams Lea seeks a Machine Learning Engineer to join our team!

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

We're looking for a Machine Learning Engineer to help build and scale our AI‑driven solutions for high‑impact clients in the legal and investment banking sectors. This role is part of a growing global engineering team, contributing to the development and delivery of cloud‑native, automated AI services that are transforming how regulated industries operate.

As a Machine Learning Engineer, you'll be hands‑on — designing, coding, and deploying ML systems while working closely with DevOps, data science, and platform engineering teams. You'll also play a key role in building out our ML engineering and operations capability, with the opportunity to coach and upskill junior engineers.

We're looking for someone with a solid foundation in engineering, a passion for solving complex problems with AI, and the curiosity to keep learning and pushing boundaries.

Key Responsibilities

• Machine Learning Development Support: Assist in designing, developing and deploying ML models and algorithms under the guidance of senior engineers to address client challenges across a range of sectors
• Cloud & MLOps Support: Help implement ML solutions on AWS (with emphasis on Amazon SageMaker). Contribute to building and maintaining CI/CD pipelines using infrastructure‑as‑code tools such as AWS CloudFormation and Terraform to automate model training and deployment
• Algorithm Implementation & Testing: Write clean, efficient and modular Python code using libraries such as pandas, NumPy, and scikit‑learn to implement ML algorithms and data pipelines. Conduct model evaluations using metrics like accuracy, precision, and recall. Run experiments, document results, and iterate to improve performance
• Collaboration & Communication: Work closely with data scientists, ML engineers and DevOps teams to integrate models into production. Participate in sprint planning, stand‑ups, and client calls to deliver technical updates in a clear and concise manner
• Quality, Documentation & Compliance: Maintain thorough documentation of data pre‑processing steps, model parameters and deployment workflows. Follow data security best practices and ensure compliance with confidentiality requirements for highly sensitive data. Provide guidance and coaching to junior engineers. Share best practices and contribute to scaling our ML engineering capability

Required Qualifications & Experience

• Education: Bachelor's degree in Computer Science, Engineering, Data Science or a closely related discipline
• Experience: 2-5 years of professional experience in machine learning, AI engineering, or software development with ML exposure
• Programming & ML Skills: Proficiency in Python (including pandas, NumPy, scikit‑learn). Basic understanding of ML concepts and model evaluation techniques
• Cloud & DevOps Familiarity: Hands‑on experience with AWS (particularly SageMaker), and an understanding of cloud‑based ML workflows. Familiarity with DevOps tools (e.g., Git, Docker) and infrastructure‑as‑code tools such as CloudFormation or Terraform
• Soft Skills: Strong analytical thinking, problem‑solving aptitude and clear written/verbal communication. Demonstrated ability to learn quickly and work in a client‑focused setting

Preferred (Additional) Experience

• Domain Knowledge: Any exposure to regulated industries involving document classification, contract analysis or predictive analytics will be advantageous.
• Tools & Frameworks: Familiarity with version control (Git), experience working in an agile development environment using tools like JIRA, and additional MLOps frameworks (e.g. MLflow, Kubeflow) or data processing technologies (e.g. Apache Spark).

Key Traits for Success

• Strong analytical thinking and a problem‑solving mindset
• A naturally curious self‑learner who is comfortable exploring new technologies
• Excellent communication skills and the ability to collaborate across global teams
• A passion for building reliable, scalable, and secure ML systems that deliver real‑world value

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 TVs, 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 [e-mail] (we do not accept applications to this email address).

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