Publié hier
Software Engineer, ML Ops
@ AeroVect
Toronto, Ontario
En bref
AeroVect is hiring a full-time Software Engineer for ML Ops to build data pipelines and dataset tooling for its autonomous ground handling fleet. The role covers ingesting field sensor data, curating versioned datasets, and optimizing training workflows on the cloud. The position is based onsite in Toronto.
Responsabilités :
- Build and maintain data pipelines for fleet field data
- Convert raw data into versioned, curated datasets
- Set up training workflows and optimize cloud costs
- Build tooling for perception engineers' workflows
- Generate metrics and diagnostics for datasets and pipelines
Résumé des exigences :
- Bachelor's or Master's in computer science, robotics or related field
- Strong Python proficiency and working knowledge of ROS2
- Working knowledge of Docker and DevOps tools
- Familiarity with AWS cloud storage and compute
- Understanding of ML workflows and dataset versioning
Outils et compétences
Source et dates
Site carrière / système de candidatures · ashby
- Date publiée par l’employeur
- 2026-11-06
- Première détection par notre source
- 2026-11-06
- Mise à jour du dossier source
- 2026-11-06
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Intermédiaire |
| Domaine | Développement logiciel |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
| Formation | Baccalauréat (exigé), Maîtrise (préféré) |
| Domaines d’études | Computer Science, Robotics, Data Engineering |
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.
| Champ | Valeur |
|---|---|
| Secteur | Airlines and Aviation |
| Taille | 51-200 employees |
| Siège social | South San Francisco, California |
| Type d’organisation | Privately Held |
| Fondée en | 2020 |
| Spécialités | AviationAutonomous DrivingAerospaceTransportationLogisticsAirport AutomationPhysical AIand Artificial Intelligence |
| Offres sur Jobsy | 17 |
| Voir la page |
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.
You will
Build and maintain data pipelines to ingest field data (rosbags, sensor logs, telemetry) from our fleet
Convert raw field data into curated, versioned datasets for the perception team and own dataset management - storage, indexing, querying, and vending datasets
Set up training workflows and optimize cloud costs
Build tooling to accelerate perception engineers' workflows - fast data access, reproducible experiments, automated evaluation pipelines
Generate metrics and diagnostics to track dataset health, model performance, and pipeline reliability
You have
Bachelor's or Master's degree in Computer Science, Robotics, Data Engineering, or a related field
Strong Python proficiency and working knowledge of ROS2
Working knowledge of docker and other DevOps tools
Familiarity with cloud storage and compute (AWS - S3, EC2, etc.)
Understanding of ML workflows and dataset versioning
We Prefer
Master's in Computer Science, Robotics, or a related discipline
2+ years of MLOps or data infrastructure experience, ideally in robotics or autonomous systems
Experience with Weights & Biases, rosbag data, and large-scale sensor datasets
Working knowledge of C/C++
Experience supporting perception or ML research teams
Please note this role will be based onsite in Toronto
Journal
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