20 meilleures offres (lead machine learning engineer, ottawa, on) (à pourvoir)

Lead Machine Learning Engineer
Serve Robotics —Ottawa, ON
- De 225 000 $ à 260 000 $ par an
- Temps plein
- Télétravail
- Doctorat
- Informatique
- Ingénierie
Innovation and AI Technical Lead
Invest Ottawa/Bayview Yards —Ottawa, ON
- De 91 200 $ à 125 400 $ par an
- Temps plein
- Travail hybride
- Systèmes PGI
- Esprit d'analyse
- Développement logiciel
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Continuous Improvement Lead
Bank of Canada —Ottawa, ON
- De 111 055 $ à 130 650 $ par an
- Travail hybride
- Bilingue
- Anglais
- Esprit d'analyse
- Assurance Dentaire
il y a 8 jours
Systems Administrator (Lead)
Rebel —Ottawa, ON
- De 90 000 $ à 130 000 $ par an
- Temps plein
- DevOps
- Windows
- AWS
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IT Operations Lead
Giatec Scientific Inc. —Ottawa, ON
- De 75 000 $ à 115 000 $ par an
- Temps plein
- Travail hybride
- Azure
- Informatique
- AWS
Postuler rapidement
il y a 9 jours
Technical Consulting Technical Leader
Cisco Systems —Ottawa, ON
- De 126 000 $ à 241 700 $ par an
- Temps plein
- Travail hybride
- Bilingue
- Vente
- Anglais
- Jours fériés payés
- Assurance Invalidité
il y a 2 jours
Lead AI Product Manager
TextLayer —Ottawa, ON
- De 200 000 $ à 240 000 $ par an
- Temps plein
- Télétravail
- Gestion de produits
- Intelligence artificielle
- Compétences en communication
Chef·fe d’équipe assurance qualité (automatisation des tests) / QA Lead (Automated Test)
Portage CyberTech —Gatineau, QC
- Temps plein
- Travail hybride
- Azure
- DevOps
- Anglais
- Assurance Dentaire
- Congés payés
Client Experience Lead, ScaleUp
Invest Ottawa/Bayview Yards —Ottawa, ON
- De 63 200 $ à 94 800 $ par an
- Temps plein
- Logiciels de GRC/CRM
- Analyse de données
- Amélioration continue
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Business Development Lead
NP Aerospace —Ottawa, ON
- De 110 000 $ à 140 000 $ par an
- Temps plein
- Microsoft Excel
- Vente
- Développement commercial
- Assurance Dentaire
- Congés payés
AI GenAI Solution Lead
Ericsson —Ottawa, ON
- De 129 500 $ à 170 100 $ par an
- Azure
- Doctorat
- Informatique
- Plan d'actionnariat des employés
- Jours fériés payés
il y a 8 jours
AI Strategy Delivery Lead – Retail - Strategy & Consulting
Accenture —Ottawa, ON
- De 142 050 $ à 292 000 $ par an
- Temps plein
- Travail hybride
- Azure
- Anglais
- AWS
Business Development Lead
NP Aerospace Limited —Ottawa, ON
- De 110 000 $ à 140 000 $ par an
- Temps plein
- Microsoft Excel
- Vente
- Baccalauréat
- Assurance Dentaire
- Assurance Vie
Responsible AI & Governance Lead – Enterprise AI Platforms - AIRLHV
NavitasPartners —Ottawa, ON
- À partir de 40 $ de l’heure
- Temps plein
- Travail hybride
- Azure
- AWS
- Intelligence artificielle
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Lead AI/ML and MLOps Consultant
gravity9 —Ottawa, ON
- Temps plein
- Télétravail
- Azure
- Vente
- AWS
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Lead Product Manager - AI Developer Platform
Scribd, Inc. —Ottawa, ON
- De 141 000 $ à 256 500 $ par an
- Temps plein
- AWS
- Gestion de produits
- APIs
- Assurance Invalidité
- Assurance Dentaire
Lead Java Developer/Architect
gravity9 —Ottawa, ON
- Temps plein
- Télétravail
- Java
- AWS
- Esprit d'analyse
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SOAR Service Lead
Pwc Canada —Ottawa, ON
- De 84 700 $ à 134 700 $ par an
- Temps plein
- Travail hybride
- Informatique
- DevOps
- Baccalauréat
Contract Manager - Commercial Lead
CAE Inc. —Ottawa, ON
- Temps plein
- Bilingue
- Anglais
- Baccalauréat
- Plan d'actionnariat des employés
- Horaire flexible avec plage fixe
Project Leader (MD-DNPL-240009N)
Nortak Software Ltd. —Ottawa, ON
- Travail hybride
- Azure
- Informatique
- DevOps

Je souhaite recevoir la dernière alerte emploi pour les postes de ce type : lead machine learning engineer (ottawa, on)

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Lead Machine Learning Engineer

Serve Robotics -
Ottawa, ON

Postuler dès maintenant

Détails du poste

Temps plein
De 225 000 $ à 260 000 $ par an

Profil recherché

Node.js
Doctorat
Informatique
Ingénierie
Maîtrise
Apprentissage automatique
Agile
Entraînement de modèle
Électrotechnique
Robotique
Évaluation de modèle
Python

Description complète du poste

At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.

The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.

Who We Are

We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.

This role develops and scales large-scale machine learning training systems for multimodal robotics data, enabling the creation of high-performance autonomy models. By optimizing distributed training pipelines, neural network architectures, and data processing workflows, the position improves training efficiency, accelerates model iteration, and maximizes GPU utilization. The role collaborates closely with ML researchers and infrastructure teams, influencing the design, deployment, and performance of end-to-end autonomy models and the large-scale data pipelines that support them.

Responsibilities

Design and maintain training systems that can process and learn from petabyte-scale multimodal datasets (e.g., video and point cloud data). This includes ensuring data is efficiently loaded, distributed, and processed across large GPU clusters.
Identify and resolve bottlenecks in the training pipeline, including data loading, preprocessing, model computation, and inter-node communication, to maximize GPU utilization and reduce training time.
Work with the ML team to develop and refine neural network architectures suitable for autonomy tasks, particularly those handling high-dimensional and sequential sensor data.
Create and adjust loss functions and training strategies that help the model learn effectively from complex multimodal inputs and improve autonomy performance.
Configure, monitor, and maintain large-scale distributed training jobs across multiple machines and GPUs, ensuring stability, fault tolerance, and efficient resource usage.
Implement scalable systems to preprocess, transform, and augment large robotics datasets so that they are suitable for model training.
Work closely with ML scientists and other engineers to integrate new models, experiments, and training approaches into the production training pipeline.
Analyze training metrics, model outputs, and experiment logs to assess model performance and guide improvements in architecture, data usage, or training strategies.
Develop tools and workflows that allow teams to run experiments, track results, and iterate quickly on new model ideas or training approaches.

Qualifications

Master’s or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline.
Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
Hands-on experience training machine learning models across multiple GPUs or compute nodes, including familiarity with distributed training frameworks and large dataset handling.
Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
Solid knowledge of core concepts such as neural networks, optimization algorithms, loss functions, model evaluation, and training methodologies.

What Makes You Stand out

Experience identifying and resolving training bottlenecks related to compute utilization, memory usage, and data throughput in machine learning systems.
Experience training machine learning models on robotics or autonomous driving datasets involving multimodal sensor inputs such as camera video, LiDAR point clouds, radar, or telemetry data.
Experience developing models that combine multiple data modalities (e.g., images, point clouds, and structured sensor data) into a unified learning system.
Peer-reviewed publications or significant research contributions in machine learning, robotics, or related areas.

Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada
Canada - ALL: $177k - $215k CAD

Compensation Range: $225K - $260K

Postuler dès maintenant

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lead machine learning engineer emplois - ottawa, on

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Je souhaite recevoir la dernière alerte emploi pour les postes de ce type : lead machine learning engineer (ottawa, on)

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