Advanced Machine Learning Engineer for AI Model Deployment
9 hours ago
Frontera Health seeks a highly skilled and motivated ML Engineer to join our expanding team in India. This role is crucial in taking research to production, ensuring our cutting-edge machine-learning models are efficiently developed, deployed, and maintained at scale.
Key Responsibilities- Model Deployment and Productionization: Lead the design, development, and deployment of machine learning models to production environments, ensuring smooth productionization of code that meets high standards of scalability and reliability.
- Code Optimization: Productionize code for various ML models (Video LLM, Computer Vision, Audio Models, etc.) and contribute to their seamless integration into production systems.
- Collaboration and Communication: Work closely with researchers in India and engineering teams in the US to ensure smooth knowledge transfer, alignment on project goals, and seamless model deployment.
- Troubleshooting and Debugging: Proactively identify, diagnose, and resolve issues in production environments to ensure minimal service disruptions.
- MLOps Best Practices: Develop and maintain CI/CD pipelines for automated model deployment, and ensure that version control practices using Git are followed consistently.
To succeed in this role, you will need:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 5+ years of experience in software engineering, with a strong focus on productionizing code and deploying machine learning models.
- Proficiency in Python programming, including relevant ML libraries like scikit-learn, TensorFlow, and PyTorch.
- Experience with CI/CD pipelines and automation tools for continuous integration and deployment.
- Solid understanding of Object-Oriented Programming (OOP) principles.
- Hands-on experience with version control systems such as Git.
- Expertise in cloud platforms like AWS, Azure, or GCP for deploying and scaling machine learning models.
This role offers a competitive salary of 40 lakhs per year, plus benefits, PTO, and stock options.
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