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Software Engineer, Systems ML

Pay
$154,003–217,000/year — pay source
**Public Compensation:** $154,003/year to $217,000/year + bonus + equity + benefits **Industry:** Internet
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Work setting
Not stated
Employment
Not stated

What you’ll work on

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

From the employer’s posting
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

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 6+ years of experience in software engineering with a focus on machine learning systems, AI infrastructure, or high-performance computing
  • Experience developing and optimizing ML training or inference pipelines using frameworks such as PyTorch, TensorFlow, or equivalent
  • Experience with distributed computing architectures and large-scale systems design for ML workloads
  • Experience programming in C++ and Python for performance-critical systems
  • Experience using profiling and performance analysis tools to identify and resolve bottlenecks in ML or compute-intensive systems

Preferred experience

  • Experience optimizing large-scale ranking and recommendation model inference on AI accelerator hardware
  • Experience with hardware-software co-design, including numerics optimization and SIMD or vectorization techniques
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience with GPU programming using CUDA, ROCm, or equivalent hardware accelerator kernel development
Qualification wording
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
Education & alternatives
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
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Posting record

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Status in our records
Live
First seen by us
Aug 28, 202672 days ago
Recorded sightings
10
Last seen by us
Nov 8, 2026
Employer says posted
Jul 8, 2026

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.

How this job compares

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.

Time since we first saw it

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.

Meta is hiring

906 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Scientist hiring has slowed
  • Takes jobs down at a usual pace
Hiring record

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  • C++
  • Python
  • PyTorch
  • TensorFlow
Where the posting names them
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

Your next step

Complete your application on www.metacareers.com. The employer’s form will show what is required.

Already applied? Track this application

Has Meta posted this job before?

Yes. We’ve followed 25 other Software Engineer, Systems ML jobs there since October 2026. All 25 are still up.

  1. This jobUp 72 days so far, first seen Aug 28
  2. DoverStill up after 26 days, first seen Oct 14
  3. BoiseStill up after 26 days, first seen Oct 14
  4. ConcordStill up after 26 days, first seen Oct 14
  5. Menlo ParkStill up after 14 days, first seen Oct 25
  6. RedmondStill up after 5 days, first seen Nov 3
  7. BellevueStill up after 5 days, first seen Nov 3
  8. SeattleStill up after 0 days, first seen Nov 8
  9. New YorkStill up after 0 days, first seen Nov 8

Large employers often post one title for several teams, so these can be separate openings.

About Meta

People
About 78,865 in 2025, up 6% from the year before.Annual report (SEC Form 10-K)
Company
Listed as META.
H-1B visas
3,530 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Layoff notices
Notices this year and last cover 3,792 people. The latest was filed May 22, 2026.State WARN notices

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,803.
August 17Last week

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.

About the role

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.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

**Summary:** Meta is seeking a Software Engineer to join our Systems ML Engineering team, focused on building and optimizing the machine learning infrastructure that powers Meta's products at massive scale. In this role, you will design and develop high-performance ML systems, working across the full stack from model training and inference pipelines to hardware-aware optimizations. You will collaborate with researchers, platform engineers, and product teams to accelerate ML workloads and improve the efficiency of AI infrastructure that serves billions of users. **Required Skills:** Software Engineer, Systems ML Responsibilities: 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 4. Architect and evaluate trade-offs in ML system design, including memory bandwidth, compute utilization, and I/O throughput 5. Partner with research and product teams to translate ML model requirements into efficient infrastructure solutions 6. Define and track system-level metrics and service level objectives to maintain production reliability of ML serving systems 7. Lead technical design reviews and contribute to engineering standards for ML systems across the organization 8. Mentor other engineers on ML infrastructure best practices, debugging methodologies, and performance optimization techniques 9. Drive adoption of AI-augmented development workflows to expand engineering productivity and broaden the scope of deliverables 10. Contribute to staged rollout strategies using feature flagging and experimentation frameworks to safely deploy ML system changes **Minimum Qualifications:** 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 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 **Preferred Qualifications:** Preferred Qualifications: 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 21. Experience with ML compiler technologies such as MLIR, LLVM, TVM, XLA, or IREE 22. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 23. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) **Public Compensation:** $154,003/year to $217,000/year + bonus + equity + benefits **Industry:** Internet **Equal Opportunity:** Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
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Pay
**Public Compensation:** $154,003/year to $217,000/year + bonus + equity + benefits **Industry:** Internet
Location & working pattern

Sunnyvale, CA

Working pattern and location restrictions need checking in the full posting.

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