Machine Learning Engineer - Efficient Machine Learning

Key Skills

Aartificial intelligence, C Programming, C++, Deep Learning, Effective communication skills, Machine learning techniques, Python Programming, PyTorch, TensorFlow

Job Description

Bose Research is searching for an outstanding machine learning engineer working on efficient deep learning to join our research team. The ideal candidate will have several years of experience crafting deep learning solutions and a proven track record, as well as a strong understanding of the fundamentals of software development and engineering principles. You should have a passion for pushing the boundaries of what can be achieved with AI and a deep understanding of computer science fundamentals. Background in pruning, quantization, NAS, efficient backbones, knowledge distillation, and so on, is expected.

Responsibilities:

• Design, implement, deploy and optimize deep learning models, data structure and algorithms on resource-constrained devices.
• Research, design and implement novel methods for efficient deep learning (e.g., quantization, pruning, NAS, knowledge distillation) with a focus on audio-related problems.
• Train and evaluate deep learning models to enable new experiences on our headphones, earbuds, soundbars, portable speakers and other consumer audio devices.
• Evaluate neural network hardware accelerators for low-power wearable devices, including working with various vendors’ custom toolchains, software and hardware and informing leadership teams about tradeoffs.
• Work with product engineering groups to transfer technology.
• Mentor interns/co-ops.

About You

• A master’s degree or Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, artificial intelligence, or a closely related discipline.
• Background in efficient ML techniques such as quantization, pruning, neural architecture search, knowledge distillation, efficient model architecture.
• Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or similar.
• Strong programming skills in Python, C/C++ and other programing languages.
• Excellent communication skills.

Preferred Qualifications

• Hands-on experience with building software applications and systems (e.g., embedded, desktop, cloud-based applications).
• Strong publication record in top-tier ML/AI conferences and journals.
• Strong curiosity on hardware architecture (e.g., “how does a particular neural processing unit work, and how does it influence energy efficiency?”), model development (e.g., “how to improve a model’s accuracy for a specific task?”), and software systems (e.g., “how to implement a software system that enables many AI experiences?”)
• Experience working on digital signal processing, audio deep learning, or multi-modal models that involve audio is a plus.