AI & Machine Learning Engineer

Nigel Frank; Greater London; Hybrid; GBP 67,500 - 82,500; Full time

Benefits offered by this job

Hybrid and flexible working

Cutting-edge AI projects

Professional certifications and培训

Structured career progression

Modern technologies exposure

Competitive benefits

Job summary

Nigel Frank is seeking an AI & ML Engineer at multiple levels for London (Hybrid) with Python, SQL, TensorFlow, PyTorch expertise. The role offers up to £75,000 and exposure to Azure, AWS and GCP. This is a chance to work on enterprise AI solutions and leverage advanced analytics within a collaborative tech team.

You will develop end-to-end ML pipelines, deploy models, and contribute to scalable data platforms across major cloud environments, with clear career progression and ongoing training.

Qualifications

• Commercial experience building and deploying AI/ML solutions.
• Strong Python and SQL skills.
• Experience with TensorFlow, PyTorch, Scikit-learn.
• Experience with cloud environments (Azure, AWS, GCP).
• Knowledge of data pipelines and ETL processes.
• Familiarity with MLOps and model deployment.

Responsibilities

• Build and deploy AI/ML solutions end-to-end.
• Design and implement AI/ML pipelines from data to deployment.
• Develop scalable ML pipelines and engineering frameworks.
• Train, evaluate, optimize and deploy AI models.
• Work with Azure, AWS and GCP cloud platforms.
• Collaborate with client stakeholders and delivery teams.

Skills

Python

SQL

TensorFlow

PyTorch

Scikit-learn

MLOps

Azure

AWS

GCP

Job description

AI & Machine Learning Engineer - Multiple Levels Available

London (Hybrid) - Python, SQL, TensorFlow, PyTorch - Azure, AWS & GCP - Up to £75,000

Our client is investing heavily in Artificial Intelligence and Machine Learning capabilities and is seeking talented AI professionals to join a growing technology team in London.

This is an opportunity to work on cutting‑edge AI solutions, develop enterprise‑scale machine learning applications and collaborate with highly skilled technical professionals delivering innovative outcomes for a range of organisations.

Whether you're looking to deepen your technical expertise or take on greater ownership and leadership responsibilities, this role offers exceptional development opportunities and clear career progression.

You Will Work With

• Building and deploying AI and Machine Learning solutions
• Designing and implementing end-to-end AI and ML pipelines, from data acquisition and feature engineering through to deployment and optimisation
• Developing scalable ML pipelines and engineering frameworks
• AI model training, evaluation, optimisation and deployment
• Cloud-native AI and data platforms across Azure, AWS and GCP
• MLOps tools and best practices for deployment, monitoring and governance
• Structured and unstructured datasets
• Generative AI and advanced analytics solutions
• Designing and maintaining scalable data pipelines, datasets and workflows
• Collaborating directly with client stakeholders to understand business challenges and translate requirements into AI solutions
• Working closely with technical and non-technical teams throughout programme delivery
• Cross-functional engineering, architecture and data teams
• Agile software development and delivery methodologies
• Exploring and adopting emerging AI technologies and approaches to drive innovation and business value

Benefits

• Salary up to £75,000
• Hybrid and flexible working arrangements
• Access to cutting‑edge AI projects
• Professional certifications and ongoing training
• Structured career progression opportunities
• Exposure to modern technologies and large-scale programmes
• Supportive and collaborative culture
• Opportunity to work across a variety of industries
• Competitive benefits package

Key Experience

• Experience building and deploying AI or Machine Learning solutions in a commercial environment
• Strong Python and SQL skills
• Experience using TensorFlow, PyTorch, Scikit-learn or similar frameworks
• Strong understanding of machine learning algorithms, deep learning architectures and model deployment practices
• Experience with Azure, AWS or GCP cloud environments
• Knowledge of data engineering principles including ETL processes, data pipelines and automated workflows
• Experience working with structured and unstructured data
• Understanding of MLOps tooling and best practices
• Knowledge of data governance, security and compliance principles within AI and data environments
• Strong analytical and problem‑solving abilityExperience working within Agile delivery environments
• Ability to work closely with stakeholders and translate business requirements into effective AI solutions

Desirable

• Generative AI experience
• Large Language Models (LLMs)
• LangChain or similar frameworks
• Spark, Hadoop or other big data technologies
• Experience with distributed computing, streaming platforms or workflow orchestration tools
• Experience monitoring and optimising model performance in production environments