AI Software Engineer, Systems ML - Wearables AI
Track this application
Get Started FreeMatch score against your CV
Get Started FreeTailor your resume to this job
Get Started FreeAbout interviewing at Meta
Recruiter screen, a technical screen (60-minute asynchronous challenge or paired live coding), a short culture-fit questionnaire, then a virtual onsite of about four rounds: fast-paced coding with multiple problems per round, system design scoped to level, a lighter behavioral, and an AI-enabled coding round assessing how you work with a coding assistant.
Read the full Meta interview process →Description
About
Meta is seeking an AI Software Engineer to join our Research & Development teams. Candidates should have industry experience working on AI Infrastructure related topics. The position will involve taking these skills and applying them to solve for complex AI infrastructure and systems challenges across Meta's platforms. We are hiring in multiple locations.
Responsibilities
- Apply relevant AI infrastructure and hardware acceleration techniques to build & optimize our intelligent ML systems that improve Meta’s products and experiences
- Goal setting related to project impact, AI system design, and infrastructure/developer efficiency
- Directly or influencing partners to deliver impact through thorough data-driven analysis
- Drive large efforts across multiple teams
- Define use cases, and develop methodology & benchmarks to evaluate different approaches
- Apply in-depth knowledge of how the ML infra interacts with the other systems around it
- Mentor other engineers / research scientists & improve the quality of engineering work in the broader team
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- Specialized experience in one or more of the following machine learning/deep learning domains: Hardware accelerators architecture, GPU architecture, machine learning compilers, or ML systems, AI infrastructure, high performance computing, performance optimizations, or Machine learning frameworks (e.g. PyTorch), numerics and SW/HW co-design
- Experience developing AI-System infrastructure or AI algorithms in C/C++ or Python Technical leadership experience
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Experience with recommendation and ranking models
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience with distributed systems or on-device algorithm development
- A Bachelor's degree in Computer Science, Computer Engineering, relevant technical field and 7+ years of experience in AI framework development or accelerating deep learning models on hardware architectures OR a Master's degree in Computer Science, Computer Engineering, relevant technical field and 4+ years of experience in AI framework development or accelerating deep learning models on hardware architectures OR a PhD in Computer Science, Computer Engineering, or relevant technical field and 3+ years of experience in AI framework development or accelerating deep learning models on hardware architectures
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies