Pay
In line with similar jobs
$154K–$217K against $118K–$194K, the middle half of what similar US postings state.
From 3,757 postings in the last year. Stated ranges, not salaries paid.
Sunnyvale, CA
Live, first seen by us 72 days ago**Public Compensation:** $154,003/year to $217,000/year + bonus + equity + benefits **Industry:** InternetRead the full posting
Design, build, and optimize large-scale ML training and inference systems
Develop and maintain low-latency ML infrastructure components in C++ and Python
Find and fix performance bottlenecks using profiling and benchmarking tools
Define and track SLOs to keep ML serving systems reliable in production
Lead technical design reviews and mentor engineers on ML infrastructure practices
Design, build, and optimize large-scale ML training and inference systems
Develop and maintain high-performance ML infrastructure components in C++ and Python
Identify and resolve performance bottlenecks across the ML stack using profiling, instrumentation, and benchmarking tools
Define and track system-level metrics and service level objectives to maintain production reliability of ML serving systems
Lead technical design reviews and contribute to engineering standards for ML systems across the organization
11. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
12. 6+ years of experience in software engineering with a focus on machine learning systems, AI infrastructure, or high-performance computing
13. Experience developing and optimizing ML training or inference pipelines using frameworks such as PyTorch, TensorFlow, or equivalent
14. Experience with distributed computing architectures and large-scale systems design for ML workloads
15. Experience programming in C++ and Python for performance-critical systems
16. Experience using profiling and performance analysis tools to identify and resolve bottlenecks in ML or compute-intensive systems
17. Experience optimizing large-scale ranking and recommendation model inference on AI accelerator hardware
18. Experience with hardware-software co-design, including numerics optimization and SIMD or vectorization techniques
19. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
20. Experience with GPU programming using CUDA, ROCm, or equivalent hardware accelerator kernel development
Minimum Qualifications: 11. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 12. 6+ years of experience in software engineering with a focus on machine learning systems, AI infrastructure, or high-performance computing
We found this posting on the National Labor Exchange. These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
In line with similar jobs
$154K–$217K against $118K–$194K, the middle half of what similar US postings state.
From 3,757 postings in the last year. Stated ranges, not salaries paid.
Day 72
Up longer than most. Similar jobs usually come down between day 7 and day 57.
Well past Meta’s usual: its jobs come down by about day 8.
From 10,604 similar postings that came down, and 331 of Meta’s. Coming down is not always a hire.
906 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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1. Design, build, and optimize large-scale ML training and inference systems, including distributed computing frameworks and hardware-accelerated pipelines 2. Develop and maintain high-performance ML infrastructure components in C++ and Python, ensuring reliability, scalability, and low-latency execution 3. Identify and resolve performance bottlenecks across the ML stack using profiling, instrumentation, and benchmarking tools
14. Experience with distributed computing architectures and large-scale systems design for ML workloads 15. Experience programming in C++ and Python for performance-critical systems 16. Experience using profiling and performance analysis tools to identify and resolve bottlenecks in ML or compute-intensive systems
12. 6+ years of experience in software engineering with a focus on machine learning systems, AI infrastructure, or high-performance computing 13. Experience developing and optimizing ML training or inference pipelines using frameworks such as PyTorch, TensorFlow, or equivalent 14. Experience with distributed computing architectures and large-scale systems design for ML workloads
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Yes. We’ve followed 25 other Software Engineer, Systems ML jobs there since October 2026. All 25 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
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**Public Compensation:** $154,003/year to $217,000/year + bonus + equity + benefits **Industry:** Internet
Sunnyvale, CA
Working pattern and location restrictions need checking in the full posting.
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