Machine Learning Engineer (Technical Leadership)

Meta is seeking principal engineers to join our teams in building cutting-edge products that connect billions of people around the world. The ideal candidate will have deep industry experience building and deploying machine learning systems at scale, including model development, training infrastructure, and optimization. You will work on leveraging ML models to detect and enforce content to keep the platforms safe and create a better user experience across Meta's products — from payment fraud detection and click-through rate prediction to search ranking, content enforcement, and spam detection. This role involves applying advanced ML techniques to some of the most exciting and massive-scale prediction problems on the web.
Machine Learning Engineer (Technical Leadership) Responsibilities
Drive the team's ML strategy & technical direction to pursue opportunities that advance machine learning capabilities across the organization
Design and develop end-to-end machine learning systems, from data pipelines to model training, evaluation, and deployment
Lead experimentation and A/B testing frameworks to measure and optimize model performance
Build highly scalable classifiers and ML tools leveraging deep learning, data regression, and rules-based models
Adapt and optimize machine learning methods for modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU)
Partner with research teams to translate cutting-edge ML research into production systems
Mentor and influence ML engineers across organizations, raising the bar for ML best practices
Identify new ML opportunities for the larger organization and influence staffing/prioritization of these initiatives
Effectively communicate complex ML systems and architectural decisions to technical and non-technical stakeholders

Minimum Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Experience leading projects with industry-wide impact
Experience communicating and working across functions to drive solutions
Experience in mentoring/influencing technical direction across organizations through design reviews, proposals, or architectural decisions
Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term mission
Experience in driving large cross-functional/industry-wide engineering efforts
12+ years of experience in programming languages (Python, C++, or Java) with technical background
8+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or deep learning based methods

Preferred Qualifications:

Experience applying ML Models in a revenue (Ads or E-Commerce) or user facing product environment at scale (Matching or Demand Supply)
Experience with relevant algorithms such as Learning to Rank, Gradient Boosting Machines, Random Forests, Deep Learning and similar algorithms
Knowledge of data structures and algorithms, including graph theory and optimization techniques
Experience in shipping products to millions of customers or have started a new line of product
Expertise in Recommender Systems, Ranking, Relevance, Personalization or adjacent fields of ML
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience with deep learning frameworks (Py Torch, Tensor Flow) and ML infrastructure tools
Familiarity with MLOps practices, model monitoring, and production ML systems
Experience building and optimizing large-scale model training pipelines
Experience shipping ML-powered products to millions of users or launching new ML product lines
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Publications or contributions to the ML research community

About Meta

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and Whats App further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Equal Employment Opportunity:

Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here.
Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.
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