Key Responsibilities
- Develop and maintain production-grade machine learning codebases, ensuring high-quality, efficient, and maintainable code.
- Design, implement, and deploy AI systems that meet performance, reliability, and scalability standards.
- Build, run, and modify model training, evaluation, and infrastructure workflows for benchmark-driven ML evaluation tasks.
- Collaborate with cross-functional teams to integrate AI systems with real-world data sources and deliver actionable insights.
- Participate in the development of model training and evaluation pipelines, ensuring accurate and reliable results.
- Work with data scientists and engineers to refine AI systems and improve their capabilities.
Requirements
- 3+ years of experience in machine learning engineering with a focus on AI system development.
- Expertise in machine learning frameworks such as TensorFlow and PyTorch.
- Strong proficiency in Python and software development principles (testing, version control, CI/CD).
- Experience with cloud-based infrastructure (AWS, GCP, Azure) and containerization (Docker).
- Ability to work effectively in cross-functional teams and communicate technical concepts clearly.