Job Description
Associate MLOPs Intern role requires long-term maintenance of products by preserving ML serving and scaling support, deployment, and maintenance of our state-of-the-art research and production-grade models.
Key Responsibilities:
- Develop and implement solutions for scalable and reliable deployment of ML models.
- Maintain and improve the performance, availability and scalability of our production-grade models
- Collaborate with the team to ensure seamless integration of ML models into existing products
- Contribute to the ongoing improvement of MLOps practices within the team
- Key upgrades to existing ML model serving infrastructure
Requirements
What you will bring:
- A proactive problem-solving mindset and eagerness to learn new technologies
- Exposure to libraries and toolkits for serving ML models (e.g., TensorFlow Serving, TorchServe, BentoML).
- Basic experience with cloud-based ML deployment platforms (e.g., Google Vertex AI Platform, Azure Machine Learning, etc).
- Basic understanding of containerization technologies (e.g., Docker, Kubernetes).
- Basic knowledge of software development principles, version control (Git), and working with APIs.
- Strong communication and collaboration skills.
Educational Background:
- Pursuing a degree in Computer Science, Data Science, or a related field.
