Description

You will own the ML operational lifecycle from training to production deployment.

This role is on-site.

Responsibilities

• Deploy high-throughput ML models into production environments.
• Manage and deploy custom applications, including those without Docker containers.
• Build and maintain development, testing, and production deployment pipelines.
• Provide technical guidance on NLP, Machine Learning, and Statistical Methods.

Required Skills

• 7+ years experience with a Bachelor's Degree, or 5+ years experience with a Master's Degree.
• Expert proficiency in Python.
• Experience managing ML model performance, including memory management and debugging.
• Proficiency in SQL (PostgreSQL) and NoSQL (MongoDB).
• Experience understanding the full ML development lifecycle (labeling, training, testing, deployment, monitoring).
• Experience with ML frameworks: Tensorflow, Pytorch, ONNX, Scikit-learn, Pandas.
• Experience with version control (Git) and regular expressions.
• Ability to formulate and rapidly prototype approaches and communicate trade-offs.

Key Skills

Education

Bachelor's degree