AWS ML Developer - Python, Azure Cloud

Responsibilities

AWS Cloud Computing

Design and implement ML pipelines using AWS Sage Maker, 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 Sage Maker (training, inference, pipelines, model registry).

Strong knowledge of AWS Bedrock and generative AI concepts (LLMs, prompt engineering).

Proficiency in Python and ML frameworks (Tensor Flow, PyTorch, Scikit‑learn).

Experience with AWS services Lambda, API Gateway, S3, IAM, Cloud Watch.

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$ - CA$

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