Staff Software Engineer, AI/ML Compute
Job Summary
Job Description
- 8+ years software development experience
- 5+ years testing and launching software
- 3+ years ML infrastructure experience
- Experience with model deployment, evaluation, optimization
- Data processing and debugging expertise
- Master's/PhD in relevant field
- Experience with data structures/algorithms
- Technical leadership experience
- Experience in complex, matrixed organizations
- Proficiency in GCP cloud services
- Bonus
- Equity
- Benefits
7 skills required
Job Details
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 3 years of experience with software design and architecture.
- 3 years of experience with ML infrastructure, including model deployment, evaluation, optimization, data processing, and debugging.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures/algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Proven track record of collaborating directly with customers and field teams
- Proficient in cloud services such as Compute, Storage, and Networking, preferably on GCP.
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.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $197,000-$291,000 + 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
- Partner with customers to benchmark AI/ML model performance on Google Cloud compute and overall infrastructure.
- Collaborate with internal infrastructure teams like Storage, Networking to enhance support for demanding AI workloads.
- Conduct in-depth performance profiling, debugging, and troubleshooting of training and inference workloads.
- Design and implement specialized ML solutions, effectively leveraging advanced ML infrastructure.
- Role may include up to 10% business-related travel to the customers and partners within the US.
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About The Company
A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.
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