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Publié il y a 16 jours

Senior Software Engineer, Behavior Planning

@ AeroVect

Toronto, ON · Vancouver, BC

160k–200k $/anTélétravailTemps plein3+ ans d’expérience
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En bref

AeroVect is hiring a Senior Software Engineer to design and build behavior planning systems for autonomous vehicles operating in airside ground-handling environments. The role owns key modules of the decision-making layer, spanning multi-agent interaction, rule-based and learned planning, and edge-case handling.

Salaire :

160 000 $–200 000 $ par année

Responsabilités :

  • Develop behavior planning algorithms for autonomous vehicles
  • Design and maintain C++ and Python planning code
  • Test in simulation and real-world scenarios
  • Analyze performance and implement enhancements
  • Document code, algorithms and system designs

Résumé des exigences :

  • Master's degree in Computer Science, Robotics or related field
  • Minimum 3 years of industry experience in autonomous driving or robotics
  • Proficient in modern C++ and object-oriented programming
  • Knowledge of state machines and behavior trees
  • Familiarity with A*, RRT or optimization-based planning

Outils et compétences

Source et dates

Site carrière / système de candidatures · ashby

Date publiée par l’employeur
2026-10-23
Première détection par notre source
2026-10-23
Mise à jour du dossier source
2026-10-23

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Détails du poste

NiveauSenior
DomaineDéveloppement logiciel
Expérience3 an(s) et plus
Heures par semaine40 (estimé)
Milieu de travailBureau, Chez les clients
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
FormationMaîtrise (exigé)
Domaines d’étudesComputer Science, Robotics

Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.

AeroVect

Profil d’entreprise sauvegardé

Renseignements historiques provenant d’un profil The Jobs API sauvegardé (champs LinkedIn/Crunchbase). Ils ne sont pas vérifiés en temps réel; les chiffres peuvent avoir changé. Les valeurs manquantes restent inconnues.

The Airport Automation Company

Description complète de l’entreprise

AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.

Abonnés LinkedIn
5 376
Personnes associées sur LinkedIn
63
Bureaux déclarés
  • 233 E Harris Ave, South San Francisco, California 94080, US
  • Toronto, Ontario, CA
  • Atlanta, Georgia 30308, US
  • Frankfurt, DE
  • New York, 10007, US
Catégories d’activité
  • Air Transportation
  • Robotics
  • Software
  • Logistics
  • Transportation
  • Artificial Intelligence (AI)
  • Aerospace
  • Autonomous Vehicles
  • Manufacturing
Autres noms enregistrés
  • AeroVect
Spécialités
  • Aviation
  • Autonomous Driving
  • Aerospace
  • Transportation
  • Logistics
  • Airport Automation
  • Physical AI
  • and Artificial Intelligence
Le profil indique une agence de recrutement
Non
Investissement total déclaré
27 000 000

La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.

AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.

ChampValeur
SecteurAirlines and Aviation
Taille51-200 employees
Siège socialSouth San Francisco, California
Type d’organisationPrivately Held
Fondée en2020
SpécialitésAviationAutonomous DrivingAerospaceTransportationLogisticsAirport AutomationPhysical AIand Artificial Intelligence
Offres sur Jobsy17
LinkedInVoir la page
Description

Who We Are

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

We are looking for an experienced Senior Software Engineer who can design and build best-in-class behavior planning systems for autonomous driving in structured, low-speed environments.

In this role, you'll own the design and implementation of key modules in the behavior planner — the decision-making layer that determines what the vehicle should do in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling problems in multi-agent interaction modeling, rule-based and learned decision-making, and robust handling of edge cases unique to airport ground operations.

This opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team.

You Will

  • Develop and implement advanced behavior planning algorithms for autonomous vehicles

  • Collaborate with cross-functional teams to ensure robust integration and functionality of planning systems

  • Design, write, and maintain efficient and scalable code in C++ and Python

  • Contribute to the architecture and continuous improvement of behavior planning software

  • Conduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithms

  • Analyze system performance and implement enhancements based on data and feedback

  • Maintain comprehensive documentation of code, algorithms, and system designs

  • Work closely with other engineering teams to ensure seamless coordination and development

You Have

  • Proficient in modern C++ (11/14/17) and object-oriented programming

  • Skilled in Python for rapid prototyping and testing

  • Strong in debugging, profiling, and optimizing code

  • Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning

  • Familiarity with path planning algorithms like A*, RRT, or optimization-based methods

  • Master’s degree in Computer Science, Robotics, or a related field

  • Minimum of 3 years of industry experience in autonomous driving, robotics, or a related field

We Prefer

  • Knowledge of state machines, behavior trees, and decision-making under uncertainty

  • Expertise in path planning algorithms such as A*, D*, and Rapidly-exploring Random Trees (RRT)

  • Knowledge of machine learning techniques, especially in the context of behavior prediction and planning

  • Experience with ROS / ROS2

  • Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment

  • Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigation

  • Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty

  • Master’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus

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