Machine Learning Algorithm Engineer, Silicon

1 Month ago • 5-8 Years • Artificial Intelligence • $156,000 PA - $229,000 PA

Job Summary

Job Description

This role involves researching and developing state-of-the-art camera video ML algorithms for new imaging use cases, leveraging Camera, ISP, and Machine Learning. You'll explore technical directions for new imaging experiences and architectures, collaborating with Hardware Architects, Research, Image Quality, and Software teams. Responsibilities include developing video ML algorithms, software/hardware partitioning, and hardware acceleration designs. The ideal candidate has 5+ years of experience in computer architecture and image processing, machine learning frameworks (TensorFlow, PyTorch), and C/C++ or Python programming. A master's or PhD in a relevant field is preferred. The position is based in Mountain View, CA.
Must have:
  • 5+ years experience with computer architecture
  • 5+ years experience with image processing/deep learning
  • Experience with ML frameworks (TensorFlow, PyTorch)
  • Proficiency in C/C++ or Python
  • Develop state-of-the-art camera video ML algorithms
Good to have:
  • Master's/PhD in EE, CE, or CS
  • Experience in Machine Learning algorithm and hardware design trade-off analysis
  • Real-time video use cases experience
  • Camera algorithms and architecture experience
  • Generative AI models for image/video processing experience
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
  • 5 years of experience with computer architecture concepts, including microarchitecture, cache hierarchy, pipelining, and memory subsystems.
  • 5 years of experience with image processing, machine learning based image processing, computational photography, or deep learning.
  • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Experience in C/C++ or Python programming.

Preferred qualifications:

  • Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  • 8 years of experience with image processing, machine learning based image processing, computational photography, or deep learning.
  • Experience in Machine Learning algorithm and hardware design trade-off analysis.
  • Experience in real-time video use cases.
  • Experience with camera algorithms and architecture.
  • Experience in generative AI models for image/video processing.

About the job

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

The US base salary range for this full-time position is $156,000-$229,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

  • Research and develop state-of-the-art camera Video ML algorithms for enabling new imaging use cases, leveraging Camera, ISP, and Machine Learning.
  • Explore and identify a technical direction for new imaging experiences and architecture.
  • Work closely with Hardware Architects, Research, Image Quality, and Software teams to identify and develop new Video ML algorithm, software/hardware partitioning, and hardware acceleration designs where applicable.

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