Description

You will select, fine-tune, and integrate ML and foundation models into production systems. You own the end-to-end ML lifecycle, including data, experimentation, deployment, and monitoring. You build evaluation frameworks to ensure model quality and performance. You develop data pipelines, feature engineering workflows, and model serving infrastructure. You optimize performance, cost, and scalability across cloud and compute environments. You collaborate with cross-functional teams to deliver AI-powered features.

Responsibilities

• Design and manage the end-to-end ML lifecycle from data preparation to monitoring.
• Build robust evaluation frameworks to ensure model quality and performance.
• Develop data pipelines, feature engineering workflows, and model serving infrastructure.
• Optimize performance, cost, and scalability across cloud and compute environments.
• Collaborate with cross-functional teams to deliver AI-powered features.

Required Skills

• 5+ years of experience in Machine Learning development.
• Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow).
• Experience deploying ML models into production environments.
• Ability to fine-tune and integrate foundation models.
• Strong background in NLP, LLMs, or computer vision.
• Bachelor's or Master's degree in AI, Computer Science, Math, or related field.

Preferred Skills

• Experience with MLOps and model operationalization.
• Strong technical communication skills.

Key Skills

Education

Bachelor's or Master's degrees