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Key Responsibilities
- Design, develop, and deploy machine learning models for classification, prediction, NLP, computer vision, and recommendation systems.
- Build and maintain end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and model evaluation.
- Work with large datasets and implement scalable data processing workflows using frameworks like PySpark, Hadoop, or distributed computing tools.
- Integrate ML models into production using APIs, microservices, and cloud-based ML deployment tools.
- Optimize model performance through hyperparameter tuning and algorithm refinement.
- Implement MLOps best practices, including model monitoring, versioning, and CI/CD for ML workflows.
- Collaborate with data engineers to improve data quality and availability for ML applications.
- Utilize deep learning frameworks (TensorFlow, PyTorch, Keras) to build advanced AI models.
- Conduct research on emerging AI/ML trends, tools, and techniques to enhance solution development.
- Prepare technical documentation, model reports, and deployment guides for stakeholders.
- Ensure model fairness, ethical AI practices, and compliance with data privacy standards.
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics, or a related field.
- Strong proficiency in Python, including ML libraries such as scikit-learn, pandas, NumPy, SciPy.
- Experience with deep learning frameworks: TensorFlow, Keras, PyTorch.
- Proficiency in building ML pipelines and workflow automation using MLflow, Kubeflow, Airflow, or Azure ML.
- Solid understanding of data structures, algorithms, probability, and statistics.
- Experience with cloud platforms (AWS, Azure, GCP) and ML services (SageMaker, Vertex AI, Azure ML Studio).
- Familiarity with APIs, microservices, and containerization using Docker and Kubernetes.
- Experience with NLP libraries (spaCy, HuggingFace Transformers) or computer vision tools (OpenCV).
- Knowledge of version control (Git) and CI/CD pipelines.
- Strong analytical, problem-solving, and critical thinking skills.
Key Skills
Ranked by relevance
ai
machine learning
computer vision
microservices
deep learning
tensorflow
pytorch
cloud
keras
cicd
artificial intelligence
distributed computing
containerization
data structures
kubernetes
kubeflow
python
docker
pandas
hadoop
mlflow
numpy
scipy
mlops
git
aws
gcp
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- Posted
- Dec 09, 2025
- Type
- Full-time
- Level
- Entry
- Location
- Canada
- Company
- Tek Tron IT
Industries
IT Services
IT Consulting
Categories
Engineering
Information Technology
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