Find Jobs
Find Jobs Near You – Available Work in Your Location
Software Engineer, Systems ML
Career Insights for Machine Learning Engineer
See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.
Scorecard
Based on Pennsylvania data
Review key factors to help you decide if this role fits your goals. How is this calculated?
What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$126,339 / year median in Pennsylvania
Job Description
Apply Now 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:
Design, build, and optimize large-scale ML training and inference systems, including distributed computing frameworks and hardware-accelerated pipelines Develop and maintain high-performance ML infrastructure components in C++ and Python, ensuring reliability, scalability, and low-latency execution Identify and resolve performance bottlenecks across the ML stack using profiling, instrumentation, and benchmarking tools Architect and evaluate trade-offs in ML system design, including memory bandwidth, compute utilization, and I/O throughput Partner with research and product teams to translate ML model requirements into efficient infrastructure solutions 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 Mentor other engineers on ML infrastructure best practices, debugging methodologies, and performance optimization techniques Drive adoption of AI-augmented development workflows to expand engineering productivity and broaden the scope of deliverables Contribute to staged rollout strategies using feature flagging and experimentation frameworks to safely deploy ML system changesMinimum Qualifications:
Minimum Qualifications:
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 systemsPreferred Qualifications:
Preferred Qualifications:
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 Experience with ML compiler technologies such as MLIR, LLVM, TVM, XLA, or IREE Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 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 + benefitsIndustry:
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. Apply Now Active Filters Software Engineer, Sys... Harrisburg, PA Clear All Powered By Cookie Policy We use cookies to improve your experience on our site. To find out more, read our privacy policy Accept Cookies Decline CookiesBenefits
- Dental Insurance