AI/ML Engineer

5 days ago

Canada Tek Tron IT Full time

Job Overview In this role, the Machine Learning Engineer will design, develop, and deploy AI and deep learning models for production, build scalable data pipelines for feature extraction and training, manage end‑to‑end MLOps workflows, conduct exploratory data analysis and feature engineering, collaborate with data scientists and software engineers, evaluate models with A/B testing, deploy models to cloud or containerized environments, and produce technical documentation and best‑practice guidelines. Responsibilities Design, develop, and deploy machine learning, deep learning, and AI models for production. Build and maintain scalable data pipelines for feature extraction, model training, and inference. Implement and manage end‑to‑end MLOps workflows for model versioning, monitoring, and CI/CD automation. Conduct exploratory data analysis (EDA), feature engineering, and model optimization. Work with structured and unstructured datasets, including text, images, and time‑series data. Collaborate with data scientists, software engineers, and stakeholders to translate business needs into ML solutions. Develop model evaluation processes, A/B testing, and continuous monitoring for model performance. Deploy models using cloud platforms (AWS, Azure, GCP) or containerized environments (Docker/Kubernetes). Create technical documentation, architecture designs, and ML best practice guidelines. Stay updated with the latest advancements in AI, ML, NLP, and deep learning technologies. Educational Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, Statistics, or a related field. Strong hands‑on experience with Python and ML libraries such as Scikit‑learn, TensorFlow, PyTorch, XGBoost, and LightGBM. Solid understanding of machine learning algorithms, deep learning, NLP, and model lifecycle management. Experience working with cloud ML services such as AWS SageMaker, Azure ML, and Google Vertex AI. Experience with data processing frameworks (Spark, Databricks, Airflow). Strong understanding of Linux environments, Docker, Kubernetes, and CI/CD pipelines. Experience with SQL and NoSQL databases. Familiarity with software engineering principles, version control (Git), and Agile methodologies. Seniority Level Entry level Employment Type Full‑time Engineering and Information Technology Industries IT Services and IT Consulting > #J-18808-Ljbffr

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