Description

job responsibilities include:

Designing and implementing LLM‑driven synthetic data pipelines to generate large‑scale, high‑quality training datasets.

Building and deploying generative AI models including diffusion models and LLMs to support advanced machine‑learning use cases.

Fine‑tuning and optimizing large language models for targeted downstream tasks and performance improvements.

Developing scalable data pipelines that support training, evaluation, and inference workflows end‑to‑end.

Conducting exploratory data analysis to uncover insights and identify enhancements for models or datasets.

Collaborating with researchers, engineers, and program managers to define requirements and deliver high‑impact ML solutions.

Required Qualifications:

Candidate must have a bachelor’s degree in computer science or a related technical field.

Candidate must have 2+ years of experience in machine learning or software engineering.

Having expert‑level proficiency in Python with strong capability in deep‑learning frameworks such as PyTorch.

Candidate must have proven experience working with diffusion models or large language models, along with strong analytical and debugging skills

Key Skills

Education

Any Graduate