First seen by our source: 25 days ago
RQ09508 - Sr. Machine Learning Engineer
@ Source Code
Toronto, Ontario
Overview
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.
Responsibilities:
- 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
Requirements summary:
- 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
Tools & skills
Source and dates
Source type not verified · manatal
- Employer posting date
- Not provided
- First seen by our source
- 2026-10-12
- Source record updated
- 2026-10-12
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Travel | air: none · ground: none |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Source Code
| Field | Value |
|---|---|
| Open jobs on Jobsy | 655 |
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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