Machine Learning Engineer

Zenos•San Mateo, CA

7d•Onsite

About The Position

Zenos is a highly funded next-gen AI/robotics startup, with strong customer demand. We are delivering AI productivity to the physical world. We’re attacking a trillion dollar market opportunity with a world class team at lightning speed, and having a ton of fun while doing it. This role is for someone who thrives in ambiguity, operates independently, and likes working on interesting and varied problems with smart people from places like Google, Amazon, Stanford, Carnegie Mellon, and Apple. Our founders previously started and sold a successful AI company with a nine figure exit, and our CEO has been an executive at a hyperscale tech company. Join us early and take on outsized equity ownership. This is a chance to join a top company with a unique strategy to build the next phase of AI - in the physical world. We have a fun, friendly team, and are hiring fast. We are currently in stealth mode, but excited to launch with major announcements soon.

Requirements

A track record of designing, scaling, maintaining, and iterating on robust, performant ML systems.
Ability to operate independently.
Ability to work on interesting and varied problems.
Ability to define the problem as you solve it.
Ability to work well with others to crack big challenges.
Ability to dive into multiple parts of the stack and do something that is fundamentally new.
Excitement about robotics.
Excitement about playing with small bits of hardware.

Nice To Haves

3+ years of professional experience in high-growth environments, leading technology companies, or elite research labs building and refining ML models.
Experience in perception, object recognition, reinforcement learning, and deep neural nets.

Responsibilities

Designing, scaling, maintaining, and iterating on robust, performant ML systems.
Having a key role in the foundation of our overall AI/ML roadmap.
Working with the team to set standards, define the tech stack, and mentor new hires as we scale.
Defining the problem as you solve it, and working with others to crack big challenges.
Diving into multiple parts of the stack and doing something that is fundamentally new.
Playing with small bits of hardware.