Technical Co-Founder / CTO - Zleni Robotics
Location: Toronto / GTA preferred
Stage: Pre-Seed
Role: Technical Co-Founder & CTO
Focus: Vision-Language-Action Models, Robot Learning, Manipulation
About Zleni
Zleni Robotics is building physical AI for senior care.
We’re starting with one of the most repetitive and labour-intensive workflows in senior living and long-term care: laundry handling and folding.
Our goal is not to build another robotics demo. We are building systems that can operate reliably inside real facilities, handle the variability of real laundry, and deliver measurable ROI for operators.
We are currently working with senior-care operators toward initial deployments and are looking for a deeply technical co-founder to own the robotics stack from research through production.
The Role
We’re looking for a Technical Co-Founder / CTO who is exceptional at modern robot learning and wants to turn frontier research into deployed robotics systems.
You should be deeply familiar with the rapidly evolving work in Vision-Language-Action (VLA) models, imitation learning, diffusion policies, reinforcement learning, and generalist robot policies.
You should actively follow research and releases from teams such as Physical Intelligence, NVIDIA, Google DeepMind, Stanford, Berkeley, Toyota Research Institute, and other leading robotics labs, and be capable of determining what is actually useful for production versus what is simply impressive research.
Most importantly, you need to be able to make the robot work.
Your primary technical objective will be straightforward to describe and difficult to execute:
Build a robotic system that can reliably fold real laundry in real senior-care facilities.
What You'll Own
- Own Zleni's robotics and embodied-AI technical strategy.
- Build and train VLA and robot-learning policies for deformable-object manipulation and laundry folding.
- Adapt and fine-tune state-of-the-art foundation models rather than unnecessarily rebuilding everything from scratch.
- Design data-collection and teleoperation pipelines for gathering high-quality manipulation demonstrations.
- Develop policies capable of handling variation in garments, linens, starting configurations, lighting, environments, and other real-world conditions.
- Build evaluation systems around task success rate, cycle time, intervention rate, failure recovery, and deployment reliability.
- Develop the perception, manipulation, planning, control, and inference stack required to take models from the lab into facilities.
- Work with simulation and synthetic data where they meaningfully accelerate real-world learning.
- Build mechanisms for detecting failures, recovering from them, and escalating to human teleoperation when necessary.
- Make hardware and systems decisions across arms, end effectors, cameras, compute, sensors, and supporting infrastructure.
- Deploy robots into customer facilities and personally debug problems in the field.
- Continuously evaluate new robotics research and rapidly incorporate meaningful advances into Zleni's stack.
- Recruit and lead Zleni's future robotics and engineering team.
What We're Looking For
You should have strong experience in several of the following:
- Vision-Language-Action models
- Robot foundation models
- Imitation learning / behavior cloning
- Diffusion policies
- Reinforcement learning
- Computer vision
- Manipulation and grasping
- Deformable-object manipulation
- Teleoperation and demonstration collection
- PyTorch
- ROS / ROS 2
- NVIDIA Isaac Sim / Isaac Lab
- Real-time robot control
- Sim-to-real and real-world policy deployment
You should be comfortable reading a newly released robotics paper or model, understanding the architecture and training methodology, reproducing or adapting the relevant ideas, and determining whether they can improve our system.
Experience working with models or research such as π0 / π0.5 / π0.6, NVIDIA GR00T, OpenVLA, RT-1/RT-2, ACT, Diffusion Policy, or similar approaches is particularly relevant.
What Matters More Than Credentials
We care much more about your ability to build than where you went to school.
You might be a robotics researcher, ML engineer, roboticist, graduate student, or unusually strong self-taught engineer.
A strong candidate can move comfortably between:
paper → code → robot → deployment → failure → iteration
You aren't satisfied when something works in a controlled demo. You want to understand what happens on attempt #500 in a customer facility.
You recognize that getting from 80% task success to 99%+ reliability can be a fundamentally different engineering problem than getting from 0% to 80%.
The First Mission
Your first major objective at Zleni will be to take laundry folding from prototype to deployment.
That means building a system capable of handling real-world variation across items such as towels, sheets, shirts, pants, and other common laundry while minimizing human intervention.
Success isn't a compelling demo video.
Success is a robot operating repeatedly in a senior-care facility, folding laundry reliably enough that an operator is willing to pay for it.
The Kind of Person We're Looking For
We're looking for someone who:
- Is obsessed with robotics and embodied intelligence.
- Keeps up with frontier robotics research without being asked.
- Can distinguish research novelty from deployment value.
- Moves extremely quickly from an idea or paper to an experiment.
- Is willing to spend hours debugging a robot when reality disagrees with the model.
- Thinks about reliability, latency, economics, maintainability, and customer workflows alongside model performance.
- Wants substantial ownership over both the technology and the company.
- Wants to build a category-defining physical AI company from the earliest stage.
Why Zleni
Senior care is facing growing labour and capacity constraints while advances in robot learning are finally making increasingly general manipulation systems possible.
We believe the opportunity is to connect those two trends: take frontier physical-AI research and turn it into economically valuable systems operating every day in real senior-care environments.
- We're looking for a technical co-founder who wants to help build that company from the ground up.
