Data Scientist + ML Engineer (Gen AI)

Data Scientist + ML Engineer (Gen AI)

We are looking for a highly skilled Data Scientist + ML Engineer (Generative AI) to join our team. In this role, you will be responsible for developing, fine-tuning, and applying advanced generative AI models — including diffusion models, large language models (LLMs), and other state-of-the-art architectures. You will collaborate closely with cross-functional partners in research, data engineering, and operations to deliver high-quality machine learning solutions and scalable datasets. This position requires a balance of technical depth and creative problem-solving. You should be comfortable working with large, complex datasets and possess a strong grasp of modern ML frameworks, distributed computing environments, and end-to-end data pipelines.

Design and Implement LLM-Driven Synthetic Data Pipelines: Design and build workflows using LLMs and Gen AI techniques to create high-volume, high-quality synthetic data for model training and testing.

Design, implement, and deploy machine learning models with a focus on generative AI (diffusion models, LLMs, and related architectures)

Fine-tune, evaluate, and optimize large language models for specific downstream tasks and data needs

Develop and maintain scalable data pipelines supporting training, evaluation, and inference workflows

Conduct exploratory data analysis to surface insights and identify opportunities for model or data improvement

Partner cross-functionally with researchers, engineers, and data program managers to define requirements and deliver high-impact ML solutions

Build and enhance internal tools, libraries, and automation workflows to accelerate experimentation and iteration

Bachelor's degree in Computer Science or related field from an accredited U.S. institution

2+ years of experience in Machine Learning or Software Engineering

Expert-level proficiency in Python and familiarity with deep learning frameworks such as PyTorch

Strong foundation in machine learning algorithms, data preprocessing, and evaluation techniques

Demonstrated experience working with diffusion models, stable diffusion, or large language models (LLMs)

Excellent analytical, problem-solving, and debugging skills

Strong communication and documentation skills with the ability to explain complex concepts clearly

Ability to work independently in a fast-paced, iterative development environment