Quick Overview
Job Description
About us
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.
What We’re Looking For
We are looking for top engineers that combine experience with intellectual horsepower.
Excellence: Ideally 5+ years of professional experience in top-tier startups, leading technology companies, or elite research labs designing, building, refining robust and performant ML models.
AI/ML: Experience in perception, terrain mapping, proprioception, object recognition, segmentation, action planning, VLAs, reinforcement learning, and deep neural nets.
Ownership: Given our early stage, your scope will be expansive. You'll have a key role in the foundation of our overall AI/ML roadmap. You will work with the team to set standards, define the tech stack, and mentor new hires as we scale.
Dynamism: You enjoy defining the problem as you solve it, and work well with others to crack big challenges. You’re not afraid to dive into multiple parts of the stack and do something that is fundamentally new. You're excited about robotics, and playing with small bits of hardware.
The Perks
Competitive salary + significant equity: you to own a part of what we're building together
Whatever resources you need: Blackwell GPUs, etc.
Relocation support, 100% health coverage, daily lunches
Location
Our HQ is in San Mateo, 25 minutes from San Francisco and Mountain View, walking distance from Caltrain. We’re building physical machines, so we aim for 5 days in-office with flexibility as needed.
Similar jobs
- TH
Machine Learning Engineer | Contract | Remote
NewAuto ApplyTech Holding
United States🇺🇸Remote10 hours agoDockerGCPAWS+12Technology - CL
Founding RL Engineer
NewAuto ApplyClera
San Francisco🇺🇸On-site16 hours agoMachine LearningLLMPyTorch+1Engineering - DI
Principal Machine Learning Scientist
NewAuto ApplyDISCO
Remote🇺🇸Remote14 hours agoMachine LearningCase ManagementStrategic PlanningTechnology - DI
Principal Machine Learning Scientist
NewAuto ApplyDISCO
Austin🇺🇸Hybrid14 hours agoMachine LearningCase ManagementStrategic PlanningTechnology - RA
Machine Learning Engineer (Physics-based)
NewAuto ApplyRoot Access
New York City🇺🇸On-site11 hours agoMachine LearningPyTorchPythonTechnology - PO
Member of Technical Staff | Machine Learning
NewAuto ApplyPoesis
Menlo Park🇺🇸Hybrid7 hours agoMachine LearningRisk ManagementTechnology - CH
Senior Machine Learning Engineer
NewAuto ApplyCheckr
Denver🇺🇸Hybrid18 hours agoRubyMLOpsMLflow+9Technology - NS
Machine Learning Lead Engineer, Machine Learning (ML) Required, Work From Home
NewAuto ApplyNext Step Systems
San Francisco, CA🇺🇸$160k - $190k/yrRemoteYesterdayMachine LearningPyTorchPythonTechnology - VT
Machine Learning Engineer - Associate
Auto ApplyVoyager Technologies, Inc.
El Segundo🇺🇸Hybrid6 weeks agoMATLABMachine LearningComputer Vision+3Technology - VT
Machine Learning Engineer - Mid-Level
Auto ApplyVoyager Technologies, Inc.
El Segundo🇺🇸Hybrid6 weeks agoMATLABMachine LearningComputer Vision+3Technology - XO
Staff Machine Learning Engineer
Auto ApplyXometry
Lexington🇺🇸Hybrid3 weeks agoAWSMLOpsMachine Learning+9Technology - XO
Staff Machine Learning Engineer
Auto ApplyXometry
Waltham🇺🇸Hybrid3 months agoAWSMLOpsMachine Learning+9Technology