Deep Learning Engineer
- Toronto, ON, Canada
- Greater Toronto Area, Canada, Canada
$60 to $80 CAD / hour · Contract
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Job details
- Pay
- $60 to $80 CAD / hour
- Job type
- Contract
- Apply by
- Posting language
- English
- Posted
Original job description
Duration: 6 months + extensions
Location: Downtown Toronto 1x/week
Rate: 60-80hr
Why Open: Expected Vacancy
We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position.
What You’ll Do
- Develop, train, evaluate, and improve ML and deep learning models.
- Work across the ML lifecycle, including data analysis, feature preparation, experimentation, training, and evaluation.
- Build PyTorch-based models for practical business use cases.
- Analyze model performance and iterate based on clear metrics.
- Build reusable training, evaluation, and inference workflows.
- Collaborate with data, product, and engineering teams.
- Document results, findings, and trade-offs clearly.
What We’re Looking For
- Hands-on experience developing ML models.
- Strong Python programming skills.
- Experience with PyTorch or similar deep learning frameworks.
- Good grasp of ML fundamentals: training, validation, evaluation, optimization, overfitting, and generalization.
- Experience gathering, cleaning, analyzing, and preparing data for ML.
- Good software engineering practices: clean code, version control, testing, and documentation.
- Strong ownership mindset and ability to drive work forward.
- Clear communication and collaboration skills.
Especially Valuable
- Experience with personalized recommendations, search, ranking, or relevance systems.
- Experience with GCP, BigQuery, SQL, Spark, Dataflow, Airflow, Kubernetes, or cloud-based ML workflows.
- Experience supporting ML models in production.
More about this job
Responsibilities
Develop, train, evaluate, and improve machine learning and deep learning models, including PyTorch models for business use cases. Build reusable model workflows, analyze performance metrics, document findings and trade-offs, and collaborate with data, product, and engineering teams.
Requirements
Requires hands-on machine learning model development, strong Python skills, experience with PyTorch or a similar framework, and a solid understanding of machine learning fundamentals and data preparation. Candidates should also demonstrate good software engineering practices, ownership, and clear communication; experience with recommendation or ranking systems, cloud data tools, and production ML is especially valuable.
Skills
- Machine Learning
- Deep Learning
- Python
- PyTorch
- Model Training
- Model Evaluation
- Data Analysis
- Feature Preparation
- Model Optimization
- SQL
- BigQuery
- Spark
- Dataflow
- Airflow
- Kubernetes
- Personalized Recommendations
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Data & Analytics
- Software
- Retail
- Engineering
Keywords
- Machine Learning
- Deep Learning
- Python
- PyTorch
- Model Training
- Model Evaluation
- Model Optimization
- Data Analysis
- Feature Preparation
- Training Workflows
- Evaluation Workflows
- Inference Workflows
- Personalized Recommendations
- Search
- Ranking Systems
- Relevance Systems
- GCP
- BigQuery
- SQL
- Spark
- Dataflow
- Airflow
- Kubernetes
- Cloud-Based ML
- Production ML
- Version Control
- Testing
- Documentation
- Retail