About the job
Why Join Faculty?
Founded in 2014, Faculty believes that AI is the pivotal technology of our era. We have partnered with over 350 global clients to enhance their performance through human-centric AI. Our impact is tangible, as detailed here.
We steer clear of fleeting trends. Our focus is on innovating, creating, and deploying responsible AI solutions that yield significant results. We offer clients extensive expertise across technical, product, and delivery domains, serving industries such as government, finance, retail, energy, life sciences, and defense.
Our business and reputation are expanding rapidly. We seek individuals who share our intellectual curiosity and aim to build a positive legacy through technology.
Join us in harnessing AI—an epoch-defining technology—where you will be empowered to envision and implement its most impactful applications.
About the Team
The process of delivering medical solutions involves complexity, cost, and risk. Faculty’s Life Sciences team is dedicated to developing AI solutions that enhance the research and commercialization of transformative therapies.
We collaborate with leading pharmaceutical companies, academic research institutions, and MedTech startups to create solutions that address critical healthcare challenges, democratizing access to health for everyone.
About the Role
As a Machine Learning Engineer, you will deliver tailored, impactful AI solutions for our diverse clientele. You will play a crucial role in transitioning machine learning from theoretical frameworks to practical applications, contributing to robust software architecture and establishing best practices. Collaborating closely with clients and cross-functional teams, you will ensure the technical feasibility and timely delivery of high-quality, production-ready ML systems.
Your Responsibilities:
- Developing and deploying production-grade ML software, tools, and infrastructure.
- Creating reusable, scalable solutions to expedite the delivery of ML systems.
- Working alongside engineers, data scientists, and commercial leaders to address significant client challenges.

