Software Engineer, Systems ML

Meta; Indianapolis (IN); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta seeks a Software Engineer for the Systems ML Engineering team to build and optimize ML infrastructure at massive scale. You will design high-performance ML pipelines, spanning training, inference, and hardware-aware optimizations, collaborating across researchers, platform engineers, and product teams.

You will lead the design reviews, mentor engineers, and push for AI-augmented workflows to expand productivity while ensuring reliable ML serving systems.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
• 6+ years of software engineering with focus on ML systems, AI infrastructure, or HPC.
• Experience with ML training/inference pipelines using PyTorch, TensorFlow, or equivalent.
• Experience with distributed computing architectures and large-scale ML systems.
• Experience in C++ and Python for performance-critical systems.
• Experience using profiling and performance analysis tools to identify bottlenecks.

Responsibilities

• 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 tools.
• Architect and evaluate trade-offs in ML system design for memory and I/O throughput.
• Partner with research/product teams to translate model requirements into infrastructure.
• Define and track system-level metrics and SLIs to maintain production reliability.
• Lead design reviews and contribute to ML system engineering standards.
• Mentor engineers on ML infrastructure best practices and performance optimization.
• Drive AI-augmented development workflows to boost productivity and scope.
• Contribute to staged rollout strategies using feature flags and experimentation.

Skills

C++

Python

Profiling tools

Distributed systems

ML infrastructure

Education

Bachelor's degree in Computer Science or related

Tools

PyTorch

TensorFlow

CUDA

MLIR

LLVM

TVM

XLA

IREE

Job description

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:

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:

1. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

2. 6+ years of experience in software engineering with a focus on machine learning systems, AI infrastructure, or high-performance computing

3. Experience developing and optimizing ML training or inference pipelines using frameworks such as PyTorch, TensorFlow, or equivalent

4. Experience with distributed computing architectures and large-scale systems design for ML workloads

5. Experience programming in C++ and Python for performance-critical systems

6. Experience using profiling and performance analysis tools to identify and resolve bottlenecks in ML or compute-intensive systems

Preferred Qualifications:

1. Experience optimizing large-scale ranking and recommendation model inference on AI accelerator hardware

2. Experience with hardware-software co-design, including numerics optimization and SIMD or vectorization techniques

3. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

4. Experience with GPU programming using CUDA, ROCm, or equivalent hardware accelerator kernel development

5. Experience with ML compiler technologies such as MLIR, LLVM, TVM, XLA, or IREE

6. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

7. 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 Aff…

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 [e-mail].