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Principal ML Engineer at Encharge AI
I have an extensive experience designing and troubleshooting complex deep learning models: convolutional neural networks, autoencoders, LSTMs, GANs, LLMs (transformers), and diffusion models, with applications ranging from image classification, object detection, semantic segmentation, speech recognition to text, image, and music generation. I am proficient in TensorFlow, and Pytorch (also playing with Jax). I have a PhD in ultra low power mixed signal deep learning hardware accelerators, and I've done research in neural network compression methods (quantization, pruning, matrix factorization, etc). I enjoy developing new algorithms, and designing software frameworks.
UC Santa Barbara
Doctor of Philosophy (Ph.D.), Computer Engineering
January 1, 2015 – January 1, 2019
UC Santa Barbara
Master’s Degree, Computer Engineering
January 1, 2013 – January 1, 2015
EnCharge AI
Principal ML Engineer
April 1, 2023 – Present
Luminous Computing
Staff Research Engineer
July 1, 2022 – March 1, 2023
Mythic
Senior Deep Learning Researcher
August 1, 2019 – July 1, 2022
Aiva Technologies
Deep Learning Researcher
June 1, 2017 – August 1, 2019
Santa Barbara, California Area
UC Santa Barbara
MS/PhD Student, Computer Engineering
September 1, 2013 – August 1, 2019
RightScale
Product Manager
August 1, 2011 – August 1, 2013
Santa Barbara, California Area
Cultural Fit Analysis
The candidate has a strong academic background (PhD from UC Santa Barbara) and has worked at several innovative AI/ML companies (EnCharge AI, Luminous Computing, Mythic, Aiva Technologies). Their career progression from Deep Learning Researcher to Principal ML Engineer demonstrates ambition and continuous growth in the ML domain. The diverse range of projects, from music generation to computer vision and LLM optimization, indicates adaptability and a broad interest in AI applications. The early career Product Manager role, while not directly technical, shows a different facet of professional experience that could contribute to a well-rounded perspective. This profile aligns well with a culture that values innovation, deep technical expertise, and continuous learning in the ML space.
Soft Skills & Operational Fit
The candidate's resume indicates strong problem-solving skills through their research and development roles, and an ability to work in complex technical environments. Their experience as a Product Manager earlier in their career suggests an understanding of product lifecycle and user needs, which can be beneficial in aligning technical solutions with business goals. However, specific soft skills like teamwork, leadership, or communication in a team setting are not explicitly detailed in the provided job descriptions.