AI & Machine Learning Engineer

Jefferson Frank

Greater London

Hybrid

GBP 67,500 - 82,500

Full time

14 days+

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Benefits offered by this job

Salary up to £75,000
Hybrid and flexible working
Cutting-edge AI projects
Professional certifications and培训
Structured career progression
Exposure to modern technologies

Job summary

Jefferson Frank in London is seeking an AI & Machine Learning Engineer at multiple levels, offering hybrid working and a salary up to £75,000. You will work on cutting-edge AI solutions, develop enterprise ML applications and collaborate with a highly skilled technical team across programmes.

This role provides clear career progression, opportunities to deepen technical expertise and to lead initiatives, while delivering impactful AI outcomes for a range of organisations.

Qualifications

  • Experience building and deploying AI or ML solutions in a commercial environment.
  • Strong Python and SQL skills are essential.
  • Experience with TensorFlow, PyTorch, Scikit-learn or similar frameworks.

Responsibilities

  • Build and deploy AI and Machine Learning solutions.
  • Design and implement end-to-end AI and ML pipelines, from data acquisition to deployment.
  • Develop scalable ML pipelines and engineering frameworks.

Skills

Python
SQL
AI/ML solutions
MLOps concepts
Agile delivery
Cloud familiarity

Tools

TensorFlow
PyTorch
Scikit-learn
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
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