Description

You will own the migration and refactoring of deep learning codebases into production-ready states. Your focus is on improving code quality, reliability, and maintainability while optimizing backend workflows and data pipelines.

Responsibilities

• Migrate and refactor existing deep learning codebases to production-ready states.
• Expand unit and integration test coverage to improve reliability.
• Optimize backend workflows, data pipelines, and ML/DL workloads.
• Support distributed training, efficient data loading, and model scaling.
• Participate in on-call support rotation for engineering infrastructure.

Required Skills

• 6+ years of experience in Python, working with large codebases.
• 3+ years of hands-on experience training deep learning models using PyTorch.
• Expertise in CI/CD practices, unit testing, and integration testing.
• Proven experience in code optimization, especially for ML/DL workloads.
• Familiarity with GPU programming and backend ML systems.
• Ability to collaborate with cross-functional teams to transform research into product.
• Strong communication and problem-solving skills.

Preferred Skills

• Experience maturing ML systems, including evaluation metrics and scalable tooling.
• Public contributions to GitHub or open-source projects.
• Master’s degree or higher in Computer Vision, Machine Learning, or a related field.

Key Skills

Education

Any Gradute