Senior AI/ML Engineer: Scalable Models & Pipelines

Meta; Burlingame (CA); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta seeks an AI/ML Engineer to design, build, and deploy large-scale machine learning systems powering its products. You will develop and optimize AI models and pipelines spanning deep learning, LLMs, and recommendation systems to solve high-impact problems for billions of users.

Work at the interface of applied research and production engineering, translating advances into reliable, scalable systems. You will mentor peers, contribute to tooling, and help ensure privacy-by-design across the ML

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 6+ years of experience designing, training, and deploying ML/DL models in production.
• 6+ years of experience with ML frameworks such as PyTorch or TensorFlow, and proficiency in Python for model development and data processing.
• Experience with large-scale distributed training and ML serving infrastructure.
• Experience designing and running online experiments (A/B testing).
• Experience communicating technical decisions to both technical and non-technical stakeholders.

Responsibilities

• Design, develop, and deploy large-scale ML models and AI pipelines across Meta's products.
• Own end-to-end design of ML systems, evaluating modeling approaches and inference frameworks.
• Profile training and serving pipelines to reduce latency and improve compute efficiency.
• Establish model evaluation frameworks with offline metrics and online experiments.
• Collaborate with PMs, data scientists, and researchers to translate requirements into ML solutions.
• Contribute to AI tooling and infrastructure, improving developer workflows.

Skills

Python

PyTorch

TensorFlow

Distributed training

A/B testing

Model deployment

Communication

Education

Bachelor's degree or equivalent

Tools

PyTorch

TensorFlow

Job description

Meta seeks an AI/ML Engineer to design, build, and deploy large-scale machine learning systems powering its products. You will develop and optimize AI models and pipelines spanning deep learning, LLMs, and recommendation systems to solve high-impact problems for billions of users.

Work at the interface of applied research and production engineering, translating advances into reliable, scalable systems. You will mentor peers, contribute to tooling, and help ensure privacy-by-design across the ML