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Waabi

Senior / Staff Machine Learning Engineer, Vehicle Dynamics

  • Seen live on Waabi's site yesterday
  • Senior
  • Remote
Pay
$241k to $320k a year USD
Location
Remote US & Canada
Open for
17+ days
First seen
Oct 18, 2026
Apply on Waabi's site (opens in a new tab)

Posting record

No flags

Open 17+ days

The posting's record, oldest first
  1. Waabi's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Waabi, so its true age is longer.

Last checked Nov 3, 2026.

How well do you match?

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What it asks of you

4+ years of experience
“MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Robotics, Controls, Mechanical/Electrical Engineering, Computer Science and/or similar technical field(s) of study.” (quoted from the posting)
PhD asked for
“MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Robotics, Controls, Mechanical/Electrical Engineering, Computer Scienc” (quoted from the posting)

What the posting discloses

Pay
$241k to $320k a year USD
The US yearly salary range for this role is: $241,000 - $320,000 USD in addition to competitive perks & benefits. (quoted from the posting)

Not stated: Real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Skills mentioned

About the role

You Will…

  • Design and develop data-driven and machine-learned approaches to vehicle control problems, bringing modern ML to a domain traditionally solved with classical methods.
  • Develop learned models of vehicle behavior and dynamics, and integrate them into the closed-loop simulation.
  • Apply machine learning to improve how the controller adapts across vehicles and operating conditions.
  • Be part of a team of multidisciplinary Engineers and Research Scientists using an AI-first approach to enable safe self-driving at scale.
  • Own problems end to end, from conceptualization and offline experimentation through simulation and on-vehicle validation.
  • Build the data pipelines, evaluation metrics, and tooling needed to measure whether a learned approach outperforms the classical baseline.
  • Participate and share ideas in technical and architecture discussions, helping define how learning and classical control coexist in a safety-critical stack.

Qualifications

  • MS/PhD or Bachelors degree with a minimum of 4 years of industry experience in Robotics, Controls, Mechanical/Electrical Engineering, Computer Science and/or similar technical field(s) of study.
  • Demonstrated depth in control theory and dynamic systems (e.g., MPC, optimal control, state estimation, system identification, kinematic and dynamic vehicle modeling).
  • Hands-on experience applying machine learning to a physical system, with real hardware in the loop rather than simulation alone.
  • Production-quality coding skill in Python and C++, and experience with deep learning frameworks such as PyTorch.
  • Solid problem solving skills using linear algebra, optimization, statistics & probability.
  • Ability to rapidly prototype and test new algorithms, and to design the experiments that prove whether they work.
  • Open-minded and collaborative team player with the willingness to help others.
  • Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.

The US yearly salary range for this role is: $241,000 - $320,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

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