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).




- Solid 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

📌 AWS ML Developer - Python, Azure Cloud (Toronto)
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