Relevant Experience & Education Highlights

Brings deep expertise in generative AI, diffusion models, and scalable ML infrastructures, strongly aligning with building large-scale foundation model training systems for Adobe's Firefly generative AI efforts.

1. Build and optimize infrastructures that power large foundation model training

Developed scalable AI platforms and distributed systems supporting generative models and LLMs.

• Built Generative AI platform leveraging LLMs, VLMs, CNNs, and distributed parallel systems at a technology services company.
• Enhanced feature encoding for pose estimation and 3D object detection using contrastive learning and deep learning generative models including VAE/GAN and diffusion models at a university research group.
• Implemented machine learning algorithms in Python to predict robot trajectories and utilized YOLO for real-time quality control at a major automotive manufacturer.

2. Architect and optimize end-to-end ML pipelines, ensuring they're scalable, efficient, and robust

Engineered CI/CD pipelines and optimizations for ML deployment on cloud platforms.

• Implemented CI/CD pipelines for seamless integration and deployment of models and systems on AWS at a major automotive manufacturer.
• Led robotics projects using Agile and Scrum methodologies to manage timelines from design to mass production at a major automotive manufacturer.
• Developed MLOps workflows with Docker for model deployment in generative AI engineering roles at a stealth startup.

3. Strong Python and deep learning engineering skills with PyTorch training and inferencing

Applied Python and deep learning frameworks to generative AI and robotics applications.

• Fine-tuned models using contrastive learning, RLHF, and neural information retrieval in Python for AI platforms at a technology services company.
• Utilized PyTorch for training and inferencing in generative AI projects matching transformer architectures and diffusion models.
• Optimized robot trajectories and parameters using Python-based ML algorithms, increasing efficiency by 11% at a major automotive manufacturer.

Requirements & Candidate Alignment