Principle ML Engineer

Location: London

As a Principle ML Engineer, you will enhance PEI's growth and achievement by improving the customer experience with intelligent, customized solutions. You will leverage the latest AI and ML technologies to ensure our customer offerings are not only enjoyable and seamless but also at the cutting edge of industry innovation.

In this role you will be working on cutting edge ML/AI projects from ideation through to production with an emphasis on maximising value delivery at a sustainable pace. This role will help establish standards and practices for ML Engineering at PEI, so we are looking for someone who is passionate about Machine Learning and the craft of ML lifecycle delivery.

We are embarking upon a transformation journey that will revolutionise the customer experience for members of the Alternative Assets community – you can help us build that future!

As a Principle Machine Learning Engineer at PEI you will...   

• Deliver the implementation and deployment of advanced machine learning models that drive significant business impact.
• Collaborate with senior stakeholders to identify and propose AI/ML solutions to complex business challenges.
• Craft the end-to-end machine learning delivery lifecycle, including sophisticated data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and production monitoring.
• Develop and enhance the tools, frameworks, and libraries that accelerate our ML product delivery and optimize our workflows.
• Play a pivotal role in our AI and ML community, fostering a culture of rigorous learning, experimentation, and mentorship.
• Drive strategic initiatives and contribute to the company's AI/ML vision and roadmap.

We'd love to hear from you if you...  

• Have an advanced degree in Computer Science, Mathematics or a similar quantitative discipline
• Are strongly proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.)   
• Excellent knowledge and experience of Python package development, including dependency management.
• Have significant experience productionising machine learning models.
• Are an expert in one of predictive modelling, AI systems, optimisation or recommendation systems.
• Have experience with distributed compute frameworks such as Spark, Ray or Dask.
• Have knowledge of DevOps technologies such as Docker/Terraform and ML Ops practices and platforms like ML Flow.
• Have proven experience with agile delivery methodologies, SCM and CI/CD.
• Have a broad understanding of data extraction, data manipulation and feature engineering techniques.
• Are comfortable with popular statistical methodologies.
• Have good communication skills.

Nice to have

• Understanding of NLP algorithms and techniques.
• Applied experience using graphs.
• Experience with Large Language Models (fine tuning, RAG, agents) especially LangChain.
• Experience with Databricks.
• Experience with cloud IaC.

Our technology stack

• Python and Jupyter Notebooks
• PySpark/Ray for processing big data
• Azure Databricks: Workflows, Asset Bundles, MLFlow
• DevOps: Terraform, Docker