Machine Learning Platform Engineer

We’re looking for a Machine Learning Platform Engineer to join our team and help build libraries and infrastructure to support modern Machine Learning workflows. This role is ideal for someone who bridges the worlds of deep learning and software engineering — and who takes pride in writing clean, scalable, and production-ready code.

Required Qualifications
- Strong understanding of deep learning concepts and proven experience in training and deploying deep neural network models in production.
- Expertise in PyTorch and TensorFlow, with hands-on experience in real-world projects.
- Solid grasp of software engineering principles, including modularity, clean code, SOLID principles, and separation of concerns.
- Proven experience writing production-grade, maintainable, and well-documented Python code.
- Proficiency in collaborative software development using Git, including workflows with pull requests and code reviews.
- Familiarity with software release processes, including versioning, changelogs, tagging, and publishing (e.g., to PyPI or Docker Hub).
- Strong ability to write clear, user-friendly documentation and conduct well-structured benchmarking of deep neural network models.

Bonus Skills (Nice to Have)
- Experience developing SDKs or Python libraries.
- Experience working with AWS services such as S3, SageMaker, or EC2.
- Familiarity with MLOps tools like MLflow, DVC, or Airflow.
- Knowledge of AutoML concepts and tools.