Python Developer at Procom
Markham, ON, Canada -
Full Time


Start Date

Immediate

Expiry Date

02 Dec, 25

Salary

0.0

Posted On

02 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, Version Control, Data Processing, Scipy, Pandas, Model Development, Numpy, Distributed Systems, Git, Docker

Industry

Computer Software/Engineering

Description

PYTHON DEVELOPER:

On behalf of our Consulting client, Procom is searching for a Python Developer for a 6 month contract-to-perm role. This position is a hybrid position with 3 days onsite at our client’s Markham, Ontario office.

PYTHON DEVELOPER - JOB DESCRIPTION:

The ideal candidate will work on developing scalable solutions using AWS Lambda, Step Functions, and SageMaker, while leveraging Python-based frameworks and libraries. The project involves integrating machine learning models into production systems and enhancing cloud architecture.

PYTHON DEVELOPER - MANDATORY SKILLS:

  • 5+ years of professional experience as a Python Developer.
  • Strong experience with AWS SDK and cloud-native/serverless services.
  • Hands-on experience with AWS SageMaker for model training and deployment.
  • Proficiency in Python data science libraries such as Pandas, NumPy, SciPy, etc.
  • Familiarity with TensorFlow, PyTorch, or other ML frameworks.
  • Experience with CI/CD pipelines, testing frameworks, and version control (Git).
  • Strong problem-solving skills and ability to work independently.

PYTHON DEVELOPER – NICE-TO-HAVE SKILLS:

  • Exposure to MLOps practices.
  • Experience with Docker and containerized deployments.
  • Knowledge of distributed systems and large-scale data processing.
  • Background in applied data science or ML model development.
Responsibilities
  • Design, develop, and maintain Python applications leveraging AWS SDK and serverless technologies.
  • Build, train, and deploy machine learning models using AWS SageMaker.
  • Work with data pipelines and transformations using Pandas and other data science libraries.
  • Collaborate with data scientists and engineers to integrate ML solutions into production systems.
  • Write clean, efficient, and well-documented code with a focus on scalability and performance.
  • Participate in code reviews, testing, and CI/CD pipelines for production deployments.
  • Contribute to the design and improvement of cloud architecture and best practices.
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