Machine Learning Engineer (Technical Leadership)

Meta; Menlo Park (CA); On-site; USD 271,000 - 347,000; Full time

Job summary

Meta is seeking a Machine Learning Engineer to join our integrity engineering team. You will build and deploy ML systems at scale, from data pipelines to model training and deployment, to help keep Meta's platforms safe and improve user experience across products.

Lead ML strategy, mentor engineers, and collaborate with research to translate cutting-edge techniques into production. Experience in large-scale prediction, distributed training, and multi-year roadmaps is highly valued.

Qualifications

• Experience leading cross-functional projects with industry-wide impact.
• Ability to plan multi-year roadmaps aligning short-term work to the long-term vision.
• Proven ability to mentor engineers and collaborate across teams.

Responsibilities

• Drive ML strategy and technical direction across the organization.
• Design end-to-end ML systems, from data pipelines to deployment.
• Lead experimentation and A/B testing to optimize model performance.
• Build scalable classifiers and ML tools using deep learning and related techniques.
• Adapt ML methods for distributed clusters, multicore SMP, and GPU.
• Collaborate with research teams to translate cutting-edge ML into production.
• Mentor ML engineers and raise the bar for ML best practices.
• Identify new ML opportunities and influence staffing and prioritization.
• Communicate complex ML architectures to technical and non-technical stakeholders.

Skills

Python/C++/Java

Leadership

ML systems

Tools

PyTorch

TensorFlow

Job description

Meta is seeking a Machine Learning Engineer to join our integrity engineering team. 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:

• Experience leading projects with industry-wide impact
• Experience communicating and working across functions to drive solutions
• Experience in mentoring/influencing engineers across organizations
• Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term vision
• 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 adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience with deep learning frameworks (PyTorch, TensorFlow) 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 WhatsApp 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.

Meta is proud to be an Equal Employment Opportunity and affirm. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E‑Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].

$271,000/year to $347,000/year + bonus + equity + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.