Publié le mois dernier
Machine Learning Developer
@ Senstar
Waterloo, Ontario
En bref
Senstar is hiring an early-career Machine Learning Developer to take machine learning from research into deployment on embedded edge platforms. The role builds data, training and deployment workflows alongside an experienced ML researcher, with hands-on work optimizing models for Texas Instruments hardware.
Responsabilités :
- Build data collection, labeling and dataset versioning workflows
- Automate model training, evaluation and packaging
- Support optimization and deployment of models to Texas Instruments embedded platforms
- Analyze and improve inference latency, memory and accuracy
- Develop Python and C++ tools to integrate and benchmark models
Résumé des exigences :
- Strong Python and C++ programming skills
- Solid machine learning fundamentals
- Experience with PyTorch, TensorFlow or similar frameworks
- Familiarity with Linux development environments
- Understanding of precision, recall, F1 and confusion matrices
Outils et compétences
Source et dates
Site carrière / système de candidatures · bamboohr
- Date publiée par l’employeur
- 2026-10-07
- Première détection par notre source
- 2026-10-08
- Mise à jour du dossier source
- 2026-10-09
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Débutant |
| Domaine | Développement logiciel |
| Heures par semaine | 40 (estimé) |
| Milieu de travail | Bureau, Laboratoire |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
| Formation | Baccalauréat (préféré), Maîtrise (préféré) |
| Domaines d’études | Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, Artificial Intelligence |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Senstar
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.
Senstar makes sense.
Description complète de l’entreprise
Senstar is a global technology leader in advanced sensing and information management systems for the protection of infrastructure and facilities. With intelligent video management, video analytics, access control and innovative perimeter intrusion detection systems, Senstar offers a comprehensive suite of proven security and risk management solutions. Senstar products have been safeguarding people, places and property for over 40 years. Keys to our success are deep industry knowledge, global reach and world-class support. Senstar can be found protecting assets in a wide range of markets including critical infrastructure, logistics, energy, corrections and transportation.
- Abonnés LinkedIn
- 11 324
- Personnes associées sur LinkedIn
- 177
- Bureaux déclarés
- 119 John Cavanaugh Dr., Ottawa, ON K0A 1L0, CA
- 13800 Coppermine Rd, Herndon, Virginia 20171, US
- Honeywellstraße 18, Maintal, Hesse 63477, DE
- 595 Parkside Drive, Waterloo, Ontario N2L 0C7, CA
- Catégories d’activité
- Information Technology
- Service Industry
- Risk Management
- Sensor
- Public Safety
- Security
- Autres noms enregistrés
- Senstar
- Spécialités
- Perimeter Intrusion Detection Systems
- Fiber Optic Sensors
- Fence Mounted Detection Systems
- Buried Cable Detection Systems
- Life Safety Emergency Call Systems
- Video Management Software
- Video Analytics
- Pipeline Protection
- Perimeter Security
- Sensor Fusion
- Common Operating Platform
- Intrusion Detection
- Security Management
- Personal Duress
- Access Control
- Critical Infrastructure Protection
- Utility Security
- Logistics Security
- Energy Security
- Correctional Facilities Protection
- Multisensor
- Security Solutions
- and LiDAR
- Le profil indique une agence de recrutement
- Non
- Investissement total déclaré
- 0
La devise et la date d’observation ne sont pas fournies; ce n’est ni une valorisation actuelle ni une ronde de financement.
Senstar is a global technology leader in advanced sensing and information management systems for the protection of infrastructure and facilities. With intelligent video management, video analytics, access control and innovative perimeter intrusion detection systems, Senstar offers a comprehensive suite of proven security and risk management solutions. Senstar products have been safeguarding people, places and…
| Champ | Valeur |
|---|---|
| Secteur | Security and Investigations |
| Taille | 201-500 employees |
| Siège social | Ottawa, ON |
| Type d’organisation | Public Company |
| Fondée en | 1981 |
| Spécialités | Perimeter Intrusion Detection SystemsFiber Optic SensorsFence Mounted Detection SystemsBuried Cable Detection SystemsLife Safety Emergency Call SystemsVideo Management SoftwareVideo AnalyticsPipeline ProtectionPerimeter SecuritySensor Fusion |
| Offres sur Jobsy | 3 |
| Voir la page |
Senstar is looking for a Machine Learning Developer to help bring machine learning from research into real-world applications on embedded edge platforms.
This is an opportunity for an early-career developer who enjoys working with machine learning, software development, automation, and embedded technologies. You'll work closely with an experienced ML researcher, helping build the tools, processes, and workflows that support everything from data collection and model training to optimization and deployment.
The role focuses on making machine learning development more efficient, reproducible, and reliable, while providing opportunities to develop hands-on experience with model optimization and deployment on constrained hardware.
Responsibilities
- Build and maintain workflows for data collection, labeling, curation, and dataset versioning.
- Develop and improve annotation workflows for video, time-series, and other sensor data using tools such as Label Studio.
- Create reproducible training, validation, and testing datasets, maintaining traceability between data, experiments, and model versions.
- Automate model training, evaluation, regression testing, and packaging.
- Develop tools and processes that improve the efficiency and reliability of machine learning development.
- Collaborate with an experienced ML researcher on model training, evaluation, calibration, and optimization.
- Support the optimization and deployment of machine learning models to Texas Instruments embedded platforms, including TIDL and related edge inference runtimes.
- Analyze and improve inference performance, including latency, memory usage, accelerator utilization, and model accuracy.
- Develop Python and C++ tools to integrate, validate, benchmark, and deploy machine learning models.
Required Skills & Experience
- Strong programming skills in Python and C++.
- Solid understanding of machine learning fundamentals.
- Experience with PyTorch, TensorFlow, or similar machine learning frameworks.
- Familiarity with Linux development environments.
- Experience working with datasets, data-processing pipelines, and model evaluation.
- Understanding of common machine learning evaluation metrics, including precision, recall, F1, and confusion matrices.
- Strong software development practices, with an interest in building maintainable, reusable, and automated tools.
- Strong problem-solving skills, attention to detail, and the ability to work collaboratively with technical teams.
- A Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Machine Learning, Artificial Intelligence, or a related field is preferred.
This position is well suited to a recent graduate or someone early in their career. Relevant academic projects, internships, research experience, and personal projects are highly valued.
Nice to Have
- Embedded systems or edge AI, including Texas Instruments processors and TIDL.
- ONNX, model conversion, quantization, pruning, or compression.
- Computer vision, signal processing, or time-series analysis.
- Label Studio or similar data annotation platforms.
- MLflow, Weights & Biases, DVC, or similar ML lifecycle tools.
- Docker, CI/CD, and automated development workflows.
- GPU or hardware-accelerated inference.
Inclusion & Accessibility
At Senstar, we are committed to fostering an inclusive, accessible workplace that values a wide range of backgrounds, perspectives, and skills. We believe that diversity and inclusion make us stronger, more innovative, and more competitive. If you require an accommodation at any stage of the recruitment or hiring process, please let us know.
AI
We may use technology, including AI-based tools, to support our recruitment process (for example, to compare applications against job requirements or to summarize interview notes). All hiring decisions are made by our hiring teams, not by automated systems.
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