Publié il y a 3 mois
Senior Machine Learning Engineer
@ GroundedAI Inc.
Vancouver, Colombie-Britannique
En bref
GroundedAI Inc. is hiring a Senior Machine Learning Engineer to build models that turn raw underground scan data into structured, trustworthy information. The role centres on 3D point cloud segmentation and detection, with some structured extraction from technical documents. The posting describes a full-time hybrid or remote arrangement with equity and support for growth.
Responsabilités :
- Build segmentation and detection models for 2D and 3D data
- Develop localization and automated quality check models
- Develop geological prediction models from limited expert input
- Contribute to structured extraction from technical documents
- Work with noisy real-world sensor data
Résumé des exigences :
- Strong applied machine learning experience in production
- Direct experience with 3D point cloud data
- Comfort with noisy, ambiguous real-world data
- Breadth in NLP or structured information extraction
- Ability to work independently without an established playbook
- Strong software engineering fundamentals and testing
Outils et compétences
Source et dates
Type de source non vérifié · recooty
- Date publiée par l’employeur
- 2026-08-23
- Première détection par notre source
- 2026-10-13
- Mise à jour du dossier source
- 2026-10-13
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Senior |
| Domaine | Développement logiciel |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau, Domicile |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
| Avantages mentionnés | Horaire flexible, Actions ou participation |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
GroundedAI Inc.
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 2 |
Senior Machine Learning Engineer, Spatial Systems
About GroundedAI
GroundedAI builds software systems that turn complex, real-world data into reliable insights. Our products operate in challenging, industrial environments where correctness, performance, and maintainability matter just as much as innovation.
We work at the intersection of software engineering, geospatial data, and spatial computing. Our focus is on shipping robust systems used by engineers in the field, not prototypes or research demos.
Role Overview
We're looking for a Senior Machine Learning Engineer to join our product engineering team and build the models that turn raw underground scan data into structured, trustworthy information.
This role is ideal for someone with strong applied machine learning experience, particularly in 3D point cloud segmentation and detection, who also has genuine breadth to contribute to structured extraction from text.
This is an applied machine learning engineering role first, with point cloud and spatial data as the core problem space.
What You'll Do
• Build models that assist in localization and automated quality checks
• Develop models for geological prediction from limited expert input
• Build segmentation and detection models for 2d and 3d model spaces
• Contribute to structured extraction from technical documents, as your breadth allows
• Work with noisy, inconsistent, real-world sensor data rather than clean benchmark datasets
• Collaborate with the engineers working on geometry and localization
• Contribute to technical discussions on model architecture, training data strategy, and what's realistic to ship near-term versus what needs a dedicated research track
What We're Looking For
Required
• Strong applied machine learning experience, including real production work, not only research or coursework
• Direct experience with 3D point cloud data: segmentation, detection, or reconstruction
• Comfort working with noisy, real-world data where the "correct" answer isn't always well defined
• Genuine breadth beyond point cloud work, ideally some experience with NLP or structured information extraction
• Ability to work independently on problems without an established playbook
• Strong software engineering fundamentals: production code quality, testing, and the ability to take a model from prototype to shipped feature
Nice to Have
• Experience with geospatial, geological, or industrial sensor data
• Familiarity with point cloud libraries and frameworks (Open3D, PyTorch3D, or similar)
• Experience building or fine-tuning LLM-based extraction pipelines
• Background in mining, tunnelling, construction, or another physical-world industrial domain
• Experience generating or working with synthetic training data for underrepresented data types
Why GroundedAI
• Own a genuinely novel technical problem with no existing playbook to follow
• Work directly on the technology that turns field data into decisions with real financial stakes for clients
• Small, senior team where your work ships to production, not a research pipeline
• Competitive compensation and equity in the early stages of a funded startup
• Flexible hybrid / remote work options
• Support for learning, experimentation, and professional growth
Journal
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