Principal Applied Scientist, OPD Hardware

Amazon; Sunnyvale (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Join a forward-thinking company as a Principal Applied Scientist, where you will lead the charge in productizing cutting-edge computer vision and machine learning technologies. This role offers the opportunity to work on innovative consumer products, including wearables and robotics, directly impacting millions of customers worldwide. Collaborate with a diverse team of engineers and scientists to solve complex challenges and bring revolutionary products to market. If you are passionate about pushing boundaries and shaping the future of technology, this is the perfect opportunity for you.

Qualifications

• PhD or Master's with 10+ years in Computer Science or ML.
• Expertise in deep learning algorithms and computer vision.

Responsibilities

• Drive vision for camera and sensor technologies across teams.
• Lead ML innovations for advanced consumer products.

Skills

Machine Learning

Computer Vision

Deep Learning

Python

C/C++

Sensor Fusion

Edge AI Optimization

Communication Skills

Education

PhD in Computer Science

Master's degree in related field

Tools

PyTorch

TensorFlow

TFLite

TVM

Job description

Principal Applied Scientist, OPD Hardware

Job ID: 2850021 | Amazon.com Services LLC - A57

Are you passionate about pushing the boundaries of computer vision and machine learning to create innovative consumer products? Join Amazon Lab126's Camera and Sensors Group in shaping the future of wearables, Echo devices, Fire TVs, and consumer robotics.

About the Role:

As a Principal Applied Scientist, you will lead cutting-edge productization of computer vision and machine learning, directly impacting millions of customers worldwide. You'll work with a diverse team of engineers and scientists to solve complex problems and bring revolutionary products to market.

Key Responsibilities:

1. Drive strategic vision and long-term roadmap for camera and sensor technologies, influencing product teams and aligning direction across technology, silicon, and devices organizations.
2. Lead groundbreaking ML/CV innovations, focusing on differentiated hardware technologies for advanced camera and sensor capabilities.
3. Architect and implement state-of-the-art ML models for edge computing in consumer products, optimizing for performance and efficiency.
4. Guide the development of next-generation AI-enabled devices, including wearables, Echo devices, Fire TVs, and robotics.
5. Collaborate with cross-functional teams to integrate ML solutions into hardware designs.
6. Mentor and develop team members, fostering innovation and technical excellence.

BASIC QUALIFICATIONS

Basic Qualifications:

• PhD, or Master's degree with 10+ years of experience in Computer Science, ML, or related field.
• 5+ years of experience building and deploying ML models for business applications, including edge AI optimization.
• Expertise in deep learning algorithms, particularly in computer vision and sensor fusion.
• In-depth knowledge of ML paradigms including traditional ML, deep learning, LLMs, and vision transformers.
• Proficiency in Python and C/C++ for ML development and low-level optimization.
• Experience with ML frameworks such as PyTorch or TensorFlow.
• Strong understanding of camera and sensor principles and operations.

PREFERRED QUALIFICATIONS

Preferred Qualifications:

• Experience with ML model optimization tools for edge inference, e.g. TFLite or TVM.
• Knowledge of ML-specific hardware architectures (e.g., TPUs, NPUs).
• Familiarity with hardware description languages (e.g., VHDL or Verilog) and/or CUDA for GPU acceleration.
• Publications in conferences/journals such as CVPR, ICCV, NeurIPS, ICML, or IEEE TPAMI.
• Track record of patents in relevant fields.
• Hardware-software co-design experience for ML acceleration.
• Strong communication skills and ability to work in a fast-paced, collaborative environment.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.