Description

You design and implement LLM-driven synthetic data pipelines and generative AI models to support large-scale training and inference workflows.

This role is on-site.

Responsibilities

• Build and deploy generative AI models, including diffusion models and LLMs, for advanced machine learning use cases.
• Fine-tune and optimize large language models to improve performance for targeted downstream tasks.
• Develop scalable data pipelines that support end-to-end training, evaluation, and inference.
• Conduct exploratory data analysis to uncover insights and identify enhancements for models or datasets.
• Collaborate with researchers, engineers, and program managers to define requirements and deliver ML solutions.

Required Skills

• 5+ years of experience in machine learning or software engineering.
• Expert-level proficiency in Python.
• Strong capability in deep-learning frameworks, specifically PyTorch.
• Proven experience working with diffusion models or large language models.
• Bachelor’s degree in computer science or a related technical field.
• Strong analytical and debugging skills.

Preferred Skills

• Experience designing synthetic data pipelines for high-quality training datasets.

Key Skills

Education

Any Graduate