Russell Tobin
JOB DESCRIPTION:
JOB Title : Data Scientist + ML Engineer (Gen AI) (NO C2C)
Location : Cupertino , CA (Remote , but needs to be onsite occasionally)
Duration : 12 months contract with possible extension
POSITION OVERVIEW:
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.
RESPONSIBILITIES:
Design and Implement LLM-Driven Synthetic Data Pipelines: Design and build work flows 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 defi ne requirements and deliver high-impact ML solutions
Build and enhance internal tools, libraries, and automation work flows to accelerate experimentation and iteration
REQUIRED EXPERIENCE AND SKILLS:
Bachelor’s degree in Computer Science or related fi eld 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
#J-18808-Ljbffr
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.
RESPONSIBILITIES:
Design and Implement LLM-Driven Synthetic Data Pipelines: Design and build work flows 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 defi ne requirements and deliver high-impact ML solutions
Build and enhance internal tools, libraries, and automation work flows to accelerate experimentation and iteration
REQUIRED EXPERIENCE AND SKILLS:
Bachelor’s degree in Computer Science or related fi eld 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
#J-18808-Ljbffr