Première détection par notre source: il y a 29 jours
RQ09508 - Sr. Machine Learning Engineer
@ Source Code
Toronto, Ontario
En bref
Source Code is hiring a Senior Machine Learning Engineer for a Downtown Toronto contract of 8+ months with possible extension. The role is hybrid, with 3 days on site and 2 days remote, and centres on NLP models such as BERT and other transformers for text classification, sentiment analysis and language understanding.
Responsabilités :
- Build and fine-tune BERT and transformer models for NLP tasks
- Preprocess text data, including tokenization and word embeddings
- Optimize model performance through hyperparameter tuning
- Adapt pre-trained models to custom datasets
Résumé des exigences :
- Deep understanding of machine learning concepts and algorithms
- Expertise in NLP and transformer-based models
- Proficiency in TensorFlow or PyTorch
- Strong Python skills with NumPy, Pandas and Scikit-learn
- Knowledge of transfer learning
Outils et compétences
Source et dates
Type de source non vérifié · manatal
- Date publiée par l’employeur
- Non fourni
- Première détection par notre source
- 2026-10-12
- Mise à jour du dossier source
- 2026-10-12
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 |
| Déplacements | avion : aucun · route : aucun |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Source Code
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 656 |
RQ09508 - Sr. Machine Learning Engineer
Downtown, Toronto
Hybrid: 3 Days onsite / 2 days remote
Contract (8+ months contract, possible extension)
Must-Haves:
- Deep Understanding of Machine Learning Concepts: Proficiency in fundamental machine learning concepts, algorithms, and techniques.
- Expertise in Natural Language Processing (NLP): Knowledge of NLP techniques and models, especially BERT and other transformer-based models, for tasks like text classification, sentiment analysis, and language understanding.
- Experience with Deep Learning Frameworks: Proficiency in deep learning libraries such as TensorFlow or PyTorch. Experience with implementing, training, and fine-tuning BERT models using these frameworks is crucial.
- Data Preprocessing Skills: Ability to perform text preprocessing, tokenization, and understanding of word embeddings.
- Programming Skills: Strong programming skills in Python, including experience with libraries like NumPy, Pandas, and Scikit-learn.
- Model Optimization and Tuning: Skills in optimizing model performance through hyperparameter tuning and understanding of trade-offs between model complexity and performance.
- Understanding of Transfer Learning: Knowledge of how to leverage pre-train ed models like BERT for specific tasks and adapt them to custom datasets.
Nice-to-Have:
- Public Sector experience
Journal
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