We’re seeking a talented Machine Learning Engineer with a strong first-principles understanding of neural networks and deep learning to collaborate with our optics and electronics teams in simulation, design, and implementation of novel optoelectronic hardware.

 

Areas of contribution

• Implementing novel machine learning algorithms on our unique hardware

• Analyzing the performance of state of the art deep learning models on our hardware

• Developing, adapting, and mapping general machine learning algorithms based on features of our hardware

• Leading a machine learning team to provide input for hardware design and implementation

Requirements

• BS/MS/PhD, or equivalent experience in CS, EE, or related fields (e.g. statistics, applied math, computational neuroscience)

• Deep passion and fundamental understanding of design, algorithms, and data structures in modern machine learning and AI


• Strong understanding of the fundamentals of neural networks and common general algorithms including RNNs, CNNs and Reinforcement Learning


• Strong analytical skills (probability, optimization, etc.)

• Experience working with large deep learning models

• Extensive knowledge of current deep learning frameworks (e.g. TensorFlow, PyTorch, etc.) - from training SOTA models to implementing custom graph operators and making low level modifications to the framework

• Excellent communication skills and ability to collaborate on a complex cross-disciplinary system

• Experience leading engineering and/or research teams from project inception to completion

• Drive to build something that hasn't been built before

You'll do well here if...

• You enjoy thoughtful discussions fueled by problem-solving and logic

• You're comfortable both leading and contributing individually

• You're excited about the future of ML hardware

• You enjoy teaching and learning from an interdisciplinary team