AI/ML System Architect, Silicon

2 Months ago • 3 Years + • Artificial Intelligence • $127,000 PA - $187,000 PA

Job Summary

Job Description

This role involves enhancing DVFS software for Generative AI, implementing energy-efficient AI software prototypes (e.g., LLMs, Multi-modal AI), exploring AI processing on mobile processors, and analyzing hardware/software profiles to identify inefficiencies. Responsibilities include developing software for future Generative AI use cases, focusing on energy efficiency in various AI models such as LLMs and text-to-image systems. The ideal candidate will have experience with AI/ML hardware (AI accelerators, GPUs) and software (Generative AI, Transformers, LLMs), coding (Python, C/C++, TensorFlow, etc.), and ideally, experience with Android OS and low-power mobile processors.
Must have:
  • Bachelor's degree in relevant field
  • 3+ years AI/ML hardware/software experience
  • Coding proficiency (Python, C/C++, TensorFlow)
  • Enhance DVFS for GenAI
  • Implement energy-efficient AI software prototypes
Good to have:
  • Master's degree
  • Android OS experience
  • Low-power mobile processor experience
  • Multimedia processing knowledge
  • Power/performance management knowledge (DVFS, etc.)
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, with an emphasis on AI/ML hardware and software, a related field, or equivalent practical experience.
  • 3 years of experience in AI/ML hardware (AI accelerator, GPU) or software (e.g., Generative AI, Transformer, LLM, Stable Diffusion, Deep Neural Networks, Convolution Neural Networks).
  • Experience with coding (e.g., Python, C/C++, TensorFlow, Java, Kotlin, SQL).

Preferred qualifications:

  • Master's degree in Electrical Engineering, Computer Engineering, Computer Science, with an emphasis on AI/ML hardware and software, a related field, or equivalent practical experience.
  • Experience in Android operating system.
  • Experience in low power mobile processors.
  • Knowledge of multimedia processing, such as image and audio.
  • Knowledge of power and performance management features (e.g., DVFS - Dynamic Voltage and Frequency Scaling, thread scheduling, clock/power gating, QoS, throttling.).

About the job

Google engineers develop the next-generation technologies that change how users connect, explore, and interact with information and one another. As a member of an extraordinarily creative, motivated and talented team, you develop new products that are used by millions of people. We need our engineers to be versatile and passionate to take on new problems as we continue to push technology forward. If you get excited about building new things and working across discipline lines, then our team might be your next career step.

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 $127,000-$187,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

  • Enhance Dynamic Voltage and Frequency Scaling (DVFS) software development for future Generative Artificial Intelligence (GenAI) use cases.
  • Implement software prototypes (codes) for AI energy efficiency (e.g., Generative AI, Large Language Model (LLM), Multi-modal, Text-to-Image, and Image Enhancement).
  • Explore energy efficient Artificial Intelligence (AI) processing on mobile processors. 
  • Analyze hardware/software profile data to identify energy/performance inefficiency areas for future AI use cases.

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