Machine Learning Engineer

Robert Walters UK; Manchester; Hybrid; GBP 70,000 - 95,000; Full time

Job summary

A leading global organization is looking for a Machine Learning Engineer to design and deploy AI solutions. This role involves working closely with data scientists and engineers on enterprise-scale projects. Key qualifications include strong programming skills in Python and experience with frameworks like TensorFlow and PyTorch. The ideal candidate will help turn complex datasets into scalable models while ensuring compliance with internal standards. This position offers a competitive salary range of £70,000 - £95,000 per annum and supports hybrid work arrangements.

Qualifications

• Strong hands-on experience deploying machine learning models into production environments.
• Solid analytical foundations with advanced knowledge of statistics, probability, and optimization techniques.
• Experience building, testing, tuning, and optimizing machine learning models.

Responsibilities

• Design, build, and productionize machine learning and Generative AI solutions.
• Develop and maintain end-to-end ML pipelines.
• Contribute to MLOps capabilities including CI/CD pipelines.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

MLOps

SQL

Tools

Docker

Kubernetes

AWS

Job description

Overview

We are partnering with a leading global organisation to recruit an experienced Machine Learning Engineer to join a highly regarded Data & Analytics function. This role offers the opportunity to work on enterprise‑scale AI and Generative AI initiatives, building production‑grade solutions that drive automation, prediction, and decision‑making across the business.

This is an excellent opportunity for someone who enjoys taking models from experimentation through to real‑world deployment, while working closely with data scientists, engineers, and senior stakeholders.

The Opportunity

As a Machine Learning Engineer, you will play a key role in designing, building, and deploying scalable machine learning and GenAI solutions. You’ll work on complex, multi‑layered datasets and contribute to model governance, evaluation, and optimisation in regulated, real‑world environments. You will also be involved in reviewing and assessing GenAI use cases from across the business and supporting robust governance and risk controls around model usage.

Key Responsibilities

• Design, build, and productionise machine learning and Generative AI solutions that meet enterprise standards for scalability, reliability, and performance
• Partner closely with data scientists to turn experimental models into well‑engineered, production‑ready systems
• Develop and maintain end‑to‑end ML pipelines, including feature engineering, training, evaluation, versioning, monitoring, and automated retraining
• Contribute to MLOps capabilities, including CI/CD pipelines, model registries, infrastructure automation, and containerised deployments
• Perform robust model evaluation, including benchmarking, drift detection, fairness analysis, and performance optimisation
• Collaborate with data engineers and architects to enhance data quality, data flows, and platform capabilities
• Lead experimentation using modern ML frameworks to assess new algorithms and technologies and make recommendations on adoption
• Support model governance processes, ensuring compliance with internal standards, documentation, transparency, and regulatory requirements
• Advise business and product teams on opportunities for automation, predictive modelling, and GenAI enablement
• Contribute to reusable ML components, internal frameworks, and engineering best practices
• Stay up to date with emerging AI trends, tooling, and foundation models to inform strategic decision‑making

About You

• You will be a strong hands‑on Machine Learning Engineer with solid analytical foundations and experience deploying models into production environments.
• Key skills and experience include:
• Strong programming skills in Python
• Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit‑learn
• Advanced knowledge of statistics, probability, and optimisation techniques
• Proven experience building, testing, tuning, and optimising machine learning models
• Comfortable working with large, complex datasets; experience with SQL and data preprocessing
• Experience or strong exposure to MLOps, including CI/CD, Docker, Kubernetes, and cloud platforms (AWS preferred)
• Understanding of Generative AI use cases and model governance or compliance processes

Robert Walters Operations Limited is an employment business and employment agency and welcomes applications from all candidates

About the job

• Contract Type: Permanent
• Focus: Data Science & AI Research
• Workplace Type: Hybrid
• Experience Level: Associate
• Location: Manchester

Salary: £70,000 - £95,000 per annum

Date posted: 19 January 2026

Consultant: Ayden Bogle

Location: Manchester, Greater Manchester, GB

Industry: Financial Services