Senior / Staff Software Engineer, ML-based Controls
- Toronto, ON
- Hybride
- Publié 20 sept. 2026
- 1 poste
241 000 $ US–320 000 $ US / année
Ouvre un site externe
- Type d’emploi
- Temps plein
- Niveau d’expérience
- Expérimenté · 5+ ans
- Formation minimale
- Baccalauréat
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
Résumé du poste
Design and develop data-driven machine learning approaches for vehicle control and integrate them into closed-loop simulations. Own the end-to-end process from conceptualization and offline experimentation to on-vehicle validation and performance evaluation.
Détails du poste
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. \n \n 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.
Ce que vous ferez
Design and develop data-driven machine learning approaches for vehicle control and integrate them into closed-loop simulations. Own the end-to-end process from conceptualization and offline experimentation to on-vehicle validation and performance evaluation.
Exigences
Requires a Bachelor's, MS, or PhD in a technical field with at least 4 years of industry experience in robotics or controls. Candidates must demonstrate proficiency in control theory, dynamic systems, and production-quality coding in Python and C++.
Avantages
• Equity incentive awards • Annual performance bonus • Competitive perks
Compétences indiquées
- Apprentissage automatique · Souhaitée
- C++ · Souhaitée
- Python · Souhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Machine learning
- Control theory
- Python
- C++
- PyTorch
- MPC
- Optimal control
- State estimation
- System identification
- Vehicle modeling
- Data pipelines
- Simulation
- Linear algebra
- Optimization
- Statistics
- Probability
- Problem Solving
- Tooling
- Electrical Engineering
- Innovation
- Algorithms
- Machine Learning
- Data Pipelines
- Artificial Intelligence
- Research
- Python (Programming Language)
- Computer Science
- Performance Metric
- Robotics
- Mechanical Engineering
- Simulations
- PyTorch (Machine Learning Library)
- C++ (Programming Language)
- Applied Machine Learning
- Open Mindset
- Deep Learning
- Linear Algebra
- Optimal Control
- Control Theories
- Dynamical Systems
- System Identification
Domaines d’emploi
- Software
- Engineering
- Technology
- Data & Analytics
- Science & Research
- Staff Software Engineer
- Machine Learning Engineer
- Software Developers
- Computer and Information Research Scientists
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