Engineering Manager – Machine Learning

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Recursion

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2013

🧬 Biotechnology

🤖 Artificial Intelligence

💊 Pharmaceuticals

💰 $150M Post-IPO Equity on 2022-10

Biotechnology • Artificial Intelligence • Pharmaceuticals

Recursion is a pioneering biopharmaceutical company that leverages advanced technology to drive the industrialization of drug discovery. It combines hardware, software, and vast datasets to decode complex biological information, aiming to create a next-generation platform for developing therapeutics. With a focus on AI and collaboration with industry leaders like Exscientia, Recursion is at the forefront of TechBio, transforming the landscape of drug discovery and development. The company is a proud founding member of BioHive, underscoring its commitment to innovation and leadership in the life sciences sector. Operating with over 60 petabytes of proprietary data and a significant pipeline, Recursion aims to radically improve lives by exploring broad therapeutic areas in partnership with other entities.

📋 Description

• You will lead a team working to build, scale, and optimize the machine learning infrastructure that powers Recursion's drug discovery platform. • The ML infrastructure team is responsible for building and operating platforms that allow data scientists and ML engineers to train, deploy, and monitor models across Recursion's massive datasets. • You will work closely with researchers and ML engineers to understand their infrastructure needs and build scalable solutions for model development, training, and deployment. • Act as a mentor, coach, and sponsor.

🎯 Requirements

• Experience in a hands-on technical role as a tech lead or a manager with a focus on infrastructure, MLOps and distributed systems. • A people-first mindset. • Demonstrated past record of learning from and teaching peers in areas of ML infrastructure, model deployment, distributed compute, GPU optimization, and MLOps system architecture • Excitement to learn parts of our ML tech stack that you might not already know. • Fluency in life sciences or drug discovery is a plus but not required to be considered.

🏖️ Benefits

• annual bonus • equity compensation • comprehensive benefits package