Senior AI/ML Engineer: Scalable Production Systems

Meta; Seattle (WA); On-site; USD 154,000 - 217,000; Full time

Job summary

Meta is seeking an AI/ML Engineer to design, build, and deploy machine learning systems powering scale across its product ecosystem. You will develop and optimize AI models and pipelines spanning deep learning, large language models, and generative AI.

You will own end-to-end ML system design, profile training/serving pipelines, and work with product managers, data scientists, and researchers to deliver measurable improvements while prioritizing privacy and reliability.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related field.
• 6+ years designing, training, and deploying ML models in production.
• 6+ years experience with PyTorch or TensorFlow and Python for ML development.
• Experience with large-scale distributed training, model optimization, and ML serving infrastructure.
• Experience designing and running online experiments (A/B testing).
• Strong written communication of technical decisions and trade‑offs.

Responsibilities

• Design, develop, and deploy large-scale machine learning models and AI pipelines across Meta's product surfaces, including ranking, recommendation, and generative AI systems.
• Own the end-to-end technical design of AI/ML systems, evaluating architectural trade‑offs and selecting modeling approaches, training strategies, and inference frameworks.
• Instrument and profile ML training and serving pipelines to identify performance bottlenecks, reduce latency, and optimize compute efficiency at scale.
• Establish and maintain model evaluation frameworks, including offline metrics, online experimentation, and monitoring to ensure production model quality and reliability.
• Collaborate with product managers, data scientists, and research scientists to translate product requirements into ML problem formulations and deliver measurable improvements to key metrics.
• Contribute to the team's AI tooling and infrastructure by building reusable components, improving developer workflows, and driving adoption of best practices in model development and deployment.
• Apply privacy-by-design principles and integrity safeguards throughout the ML development lifecycle, partnering with cross‑functional teams to meet data governance and compliance requirements.
• Mentor other engineers on ML system design, modeling techniques, and engineering craft, and actively contribute to recruiting and technical community programs.
• Use AI‑augmented development workflows to expand scope across data analysis, product thinking, and operational readiness beyond core modeling work.
• Drive staged rollouts of new models using feature flagging and A/B testing frameworks, proactively monitoring for regressions and leading incident retrospectives to prevent recurrence.

Skills

Large-scale ML models

ML pipelines

Model evaluation & monitoring

A/B testing

ML observability

ML system design

Privacy-by-design

Mentoring engineers

Cross-functional collaboration

AI tooling & infrastructure

Education

Bachelor's degree in Computer Science / Engineering

6+ years ML production experience

6+ years PyTorch/TensorFlow

Distributed training & ML serving

Online experiments (A/B testing)

Technical writing & communication

Tools

PyTorch

TensorFlow

Job description

Meta is seeking an AI/ML Engineer to design, build, and deploy machine learning systems powering scale across its product ecosystem. You will develop and optimize AI models and pipelines spanning deep learning, large language models, and generative AI.

You will own end-to-end ML system design, profile training/serving pipelines, and work with product managers, data scientists, and researchers to deliver measurable improvements while prioritizing privacy and reliability.