Senior AI/ML Engineer: Scalable Models & Pipelines

Meta; Burlingame (CA); Vor Ort; USD 154.000 - 217.000; Vollzeit

Benefits dieser Stelle

Bonus

Equity

Benefits

Zusammenfassung

Meta seeks an AI/ML Engineer to design, build, and deploy machine learning systems powering Meta’s products. You will develop AI models and pipelines at scale, spanning deep learning, LLMs, and recommender systems to solve high-impact problems across our ecosystem.

You will work at the intersection of applied research and production engineering, translating advances into reliable, scalable systems serving billions of users. This role emphasizes collaboration, governance, and measurable impact.

Qualifikationen

• Bachelor's degree or equivalent practical experience in CS/engineering.
• 6+ years designing, training, deploying ML/DL models in production.
• 6+ years with ML frameworks (PyTorch or TensorFlow) and Python for model dev.
• Experience with large-scale distributed training and ML serving infra.
• Experience designing/running online experiments (A/B) to measure impact.
• Clear written communication of technical decisions to diverse stakeholders.

Aufgaben

• Design, develop, and deploy large-scale ML models and AI pipelines across Meta products.
• Own end-to-end technical design of ML systems, including training and inference choices.
• Profile training and serving pipelines to reduce latency and improve efficiency.
• Establish evaluation frameworks with offline metrics and online experiments.
• Collaborate with product managers and data scientists to translate requirements into ML problems.

Kenntnisse

ML model design

Production ML

PyTorch

TensorFlow

Python

Distributed training

A/B testing

ML observability

Communication

Mentoring

Ausbildung

Bachelor's degree in CS/Engineering or equivalent

Tools

PyTorch

TensorFlow

Python

Jobbeschreibung

Meta seeks an AI/ML Engineer to design, build, and deploy machine learning systems powering Meta’s products. You will develop AI models and pipelines at scale, spanning deep learning, LLMs, and recommender systems to solve high-impact problems across our ecosystem.

You will work at the intersection of applied research and production engineering, translating advances into reliable, scalable systems serving billions of users. This role emphasizes collaboration, governance, and measurable impact.