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Role : AWS Sagemaker
Location : Toronto, ON (Hybrid)
Job Type : Contract
Job Description :
- Develop and implement machine learning models and data science algorithms using Python.
- Utilize SQL for data manipulation and querying.
- Build and optimize ML models using XGBoost and other relevant tools.
- Work with AWS components such as SageMaker and S3 for deploying and managing machine learning models.
- Develop and maintain Generative AI (GenAI) solutions, including Retrieval Augmented Generation (RAG) models.
- Utilize AWS Bedrock, vector databases, and embedding techniques for advanced AI solutions.
- Collaborate with cross-functional teams to integrate machine learning solutions into production systems.
- Stay updated with the latest advancements in machine learning and AI technologies.
Requirements :
Hands-on experience in machine learning and data science algorithms using Python.Proficiency in SQL.Strong knowledge and experience in building ML models using XGBoost, scikit-learn.Exposure to AWS components such as SageMaker and S3.Experience with Generative AI, including RAG models, AWS Bedrock, vector databases, and embedding techniques.Excellent problem-solving skills and attention to detail.Strong communication and teamwork abilities.Design and develop scalable and resilient systems using Java or Python to contribute to continual, iterative improvements for product teams.Execute software solutions, design, development, and technical troubleshooting.Identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture.Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems.Seniority Level : Mid-Senior level
Employment Type : Contract
Job Function :
IT Services and IT Consulting
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