Machine Learning Engineer

About This Role

Meta is seeking a Machine Learning Engineer to build and deploy ML systems that power content ranking, recommendations, ads targeting, and integrity signals across its platforms. You will work on models that serve billions of inference requests per day and directly affect the product experience for Meta's global user base.

Job Overview

• Job Title: Machine Learning Engineer
• Company: Meta
• Location: Menlo Park, CA / New York, NY / Seattle, WA / Austin, TX / Chicago, IL
• Job Type: Full-time
• Experience Level: Mid-level (2–5 years)
• Salary Range: $55–$75/hr
• Posted Date: 2026-06-01
• Application Deadline: 2026-07-01

Role Context

ML Engineers at Meta sit at the intersection of research and production. You will work with research scientists to take models from experimentation to deployed serving pipelines. Teams are responsible for the full lifecycle — data pipelines, feature engineering, model training, evaluation, and production monitoring — typically supporting one product surface like Feed, Reels, or Ads.

Key Responsibilities

• Design, train, and deploy machine learning models for ranking or recommendation tasks
• Build scalable data pipelines and feature stores to support model training at petabyte scale
• Conduct offline and online (A/B) experiments to measure model impact
• Monitor production model health and respond to regressions or anomalies
• Collaborate with research scientists to productionize experimental models
• Improve ML infrastructure tooling and training efficiency across the team

Requirements & Skills

• 2+ years of experience building and deploying ML models in a production environment
• Proficiency in Python and familiarity with PyTorch or TensorFlow
• Experience with large-scale data processing (Spark, Hive, or similar)
• Understanding of ranking, classification, and recommendation system architectures
• Strong software engineering fundamentals — clean code, testing, version control
• Experience with A/B testing frameworks and experiment analysis

Benefits & Work Conditions

• $55–$75/hr with Meta RSUs and semi-annual bonuses
• Hybrid schedule with flexibility on remote days
• $3,000 annual learning and wellness stipend
• Full health, dental, vision, and mental health coverage
• Access to Meta's internal ML infrastructure and GPU compute resources

Who Should Apply

Engineers who enjoy the challenge of building systems that are simultaneously scientifically rigorous and production-grade. You are comfortable working across data pipelines, model code, and serving infrastructure, and you care about measuring real impact through experimentation.

About the Company

Meta's AI organization includes FAIR (Fundamental AI Research) and applied ML teams that build the models powering Feed, Stories, Ads, and integrity systems. Engineers at Meta have access to some of the largest training clusters and real-time data pipelines in the industry.

How to Apply

Apply through Meta Careers. Search "Machine Learning Engineer." The process includes a coding screen, an ML system design round, and a behavioral interview assessing collaboration and impact.