Responsibilities
AWS Cloud Computing
Design and implement ML pipelines using AWS SageMaker, including data preprocessing, model training, tuning, and deployment.
Develop and integrate Generative AI applications using AWS Bedrock and foundation models (e.g., Titan, Claude, Llama).
Build APIs and microservices to expose ML models for consumption by applications.
Optimize ML workflows for cost efficiency and scalability in AWS environments.
Collaborate with data scientists and business stakeholders to translate requirements into technical solutions.
Implement security best practices for ML models and data in AWS.
Monitor and maintain deployed models, ensuring performance and reliability.
Qualifications
Hands‑on experience with AWS SageMaker (training, inference, pipelines, model registry).
Strong knowledge of AWS Bedrock and generative AI concepts (LLMs, prompt engineering).
Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit‑learn).
Experience with AWS services Lambda, API Gateway, S3, IAM, CloudWatch.
Familiarity with MLOps practices and CI/CD pipelines for ML.
Understanding of data engineering concepts and feature engineering.
Excellent problem‑solving and communication skills.
Experience:
6-8 years
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Information Technology
Industries IT Services and IT Consulting
Location: Markham, Ontario, Canada
Salary: CA$110,000.00 - CA$130,000.00
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AWS Cloud Computing
Design and implement ML pipelines using AWS SageMaker, including data preprocessing, model training, tuning, and deployment.
Develop and integrate Generative AI applications using AWS Bedrock and foundation models (e.g., Titan, Claude, Llama).
Build APIs and microservices to expose ML models for consumption by applications.
Optimize ML workflows for cost efficiency and scalability in AWS environments.
Collaborate with data scientists and business stakeholders to translate requirements into technical solutions.
Implement security best practices for ML models and data in AWS.
Monitor and maintain deployed models, ensuring performance and reliability.
Qualifications
Hands‑on experience with AWS SageMaker (training, inference, pipelines, model registry).
Strong knowledge of AWS Bedrock and generative AI concepts (LLMs, prompt engineering).
Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit‑learn).
Experience with AWS services Lambda, API Gateway, S3, IAM, CloudWatch.
Familiarity with MLOps practices and CI/CD pipelines for ML.
Understanding of data engineering concepts and feature engineering.
Excellent problem‑solving and communication skills.
Experience:
6-8 years
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Information Technology
Industries IT Services and IT Consulting
Location: Markham, Ontario, Canada
Salary: CA$110,000.00 - CA$130,000.00
#J-18808-Ljbffr
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