Machine Learning Software Engineer, Silicon
Mountain View, CA, USA; San Diego, CA, USA
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development, and with data structures/algorithms.
- 5 years of experience with design and architecture, and testing/launching software products.
- Experience with Machine Learning.
Preferred qualifications:
- PhD in Computer Science.
- Experience in running a large program or several projects simultaneously.
- Experience in computer architecture for accelerators such as Machine Learning (ML) accelerators, Graphics Processor Unit (GPU), or Digital Signal Processor (DSP).
- Understanding of how a parallelizing optimizing compiler works.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
EdgeTPU is a family of embedded Machine Learning (ML) accelerators aiming towards a broad set of applications, from smartphones to self-driving cars to data center applications. We are developing a template design to aim the broad span of speed/energy dissipation/cost trade-offs corresponding to the many devices being developed. The Compute software team makes the Edge TPU ML accelerator programmable, via tooling that includes a compiler, runtime, SDK with documentation and further tooling, and an Applied ML team that optimizes ML models for serving on device.
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 $237,000-$337,000 + 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 benefits at Google. 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 benefits at Google.Responsibilities
- Work with the hardware architecture and software compiler teams. Help identify trade-offs for flexibility vs performance to help set direction to hardware design.
- Enhance the current Tensor Processing Unit (TPU) programming model for advanced users. Design new mechanisms to support user-guided compilation to extract maximum performance out of the hardware.
Tags: Architecture Computer Science GPU Machine Learning ML models NLP PhD Research Security Testing
Perks/benefits: Career development Equity Salary bonus
More jobs like this
Explore more AI, ML, Data Science career opportunities
Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
- Open Data Science Manager jobs
- Open Marketing Data Analyst jobs
- Open Lead Data Analyst jobs
- Open Data Engineer II jobs
- Open Senior Business Intelligence Analyst jobs
- Open MLOps Engineer jobs
- Open Principal Data Engineer jobs
- Open Power BI Developer jobs
- Open Data Scientist II jobs
- Open Business Intelligence Developer jobs
- Open Data Analytics Engineer jobs
- Open Junior Data Scientist jobs
- Open Business Data Analyst jobs
- Open Sr Data Engineer jobs
- Open Data Analyst Intern jobs
- Open Product Data Analyst jobs
- Open Sr. Data Scientist jobs
- Open Senior Data Architect jobs
- Open Big Data Engineer jobs
- Open Research Scientist jobs
- Open Azure Data Engineer jobs
- Open Principal Data Scientist jobs
- Open Data Quality Analyst jobs
- Open Manager, Data Engineering jobs
- Open Data Product Manager jobs
- Open Data quality-related jobs
- Open GCP-related jobs
- Open Java-related jobs
- Open Business Intelligence-related jobs
- Open ML models-related jobs
- Open Data management-related jobs
- Open Privacy-related jobs
- Open PhD-related jobs
- Open Deep Learning-related jobs
- Open Finance-related jobs
- Open Data visualization-related jobs
- Open PyTorch-related jobs
- Open APIs-related jobs
- Open TensorFlow-related jobs
- Open NLP-related jobs
- Open Consulting-related jobs
- Open LLMs-related jobs
- Open CI/CD-related jobs
- Open Snowflake-related jobs
- Open Generative AI-related jobs
- Open Kubernetes-related jobs
- Open Hadoop-related jobs
- Open Data governance-related jobs
- Open Airflow-related jobs
- Open Docker-related jobs