Usman Bashir

Director of AI Engineering @ FIS

About

Experienced Engineering Leader with a demonstrated history of delivering Products in Machine Learning,Optimisation. Strong education professional with a Master of Science (MS) focused in Artificial Intelligence from University of Sussex.

Country

City

United Kingdom

Industry

Information Technology & Services

Skill

Software as a Service (SaaS), Azure Databricks, Data Engineering, Natural Language Processing (NLP), Systems Design, Engineering Leadership, Emerging Technologies, Financial Services, Retrieval-Augmented Generation (RAG), Generative AI, Large Language Models (LLM), Product Management, Java, Machine Learning, Software Development, Swarm Intelligence, Big Data, Apache Spark, Management, Lin Kernighan Algorithm

Experience

Director of AI Engineering

FIS

2020-11 - Present · 5 yrs 10 mos

London, England Metropolitan Area

Leader of AI Engineering Teams. Helping shape the AI/ML strategy for FIS

VP of Product & Engineering

Mobius Labs

2020-7 - 2020-10 · 4 mos

London & Berlin

Giving Superhuman AI vision to product. Leading the product and engineering teams

Consultant

Vodafone

2020-3 - 2020-5 · 3 mos

London, England Metropolitan Area

Performed a review of large transformation project by Vodafone group

VP, Research & Engineering

GTN

2018-11 - 2020-3 · 1 yr 5 mos

London, United Kingdom

I lead the Research and Engineering Function at GTN. I've built a highly scalable drug discovery product: A Platform that uses Quantum Physics and machine learning to overcome challenges in machine Learning. I've built cross functions teams/Squads, project planning, risk management system. The most enjoyable part of my job is coach, mentor and support an amazing group of people here at GTN. GTN: Using machine learning & quantum physics, @GTN_LTD is overcoming challenges in drug discovery: https://t.co/bWzbhaAOZt Drug discovery costs $2.6 billion, takes 10 years and has a 91% attrition rate. GTN are reducing the cost of drug discovery using the latest deep learning models and reinforcement learning to generate and evaluate candidate molecules. Built on Amazon Web Services (AWS), Usman Bashir walks through their data and machine learning architecture. Starting from data stored in S3 and processed using AWS Glue. To their machine learning pipeline built with open-source technologies like Kubeflow and hosted on AWS EKS. By blending spot instances and on demand they are able to reduce the cost of experimentation by 50% making more experiments financially viable. Resources: GTN research paper: https://lnkd.in/gj8R96c Pytorch: https://pytorch.org/ S3 data lake: https://lnkd.in/g7zZZXK AWS Glue: https://lnkd.in/gfvSnPu Kubeflow: https://www.kubeflow.org/ Amazon Elastic Kubernetes Service (EKS): https://lnkd.in/gnAvvRx Spot instances: https://lnkd.in/gmbfij7

AI Engineering leader, Machine Learning Engineering

QuantumBlack, AI by McKinsey

2016-4 - 2018-10 · 2 yrs 7 mos

London

Data Science and Engineering leader delivering high impact, visual, and intelligent solutions.

Engineering leader

2014-6 - 2016-3 · 1 yr 10 mos

London, United Kingdom

Lead on Various Project from LNG Trading & Operations optimisation tools, Oil Demand Prediction, Analytics Strategy and Palantir Engagement, Big data platform and data science strategy