Software Engineer, Machine Learning

Meta; Menlo Park (CA); On-site; USD 347,000 - 403,000; Full time

Job summary

Meta seeks a Software Engineer with deep machine learning expertise to drive advances across AI-powered products and platforms. You will bridge foundational ML research and large-scale production systems, shaping the technical direction of ML infrastructure, modeling, and applied AI at global scale.

You will mentor engineers, define architectural standards, improve training pipelines, inference, and data integrity, and lead cross-functional roadmaps to balance short-term delivery with long-term

Qualifications

• Bachelor's degree in Computer Science or related field, or equivalent practical experience.
• 12+ years of experience designing, building, and deploying large-scale ML systems in production.

Responsibilities

• Define and own the technical architecture of ML systems, including training pipelines, inference infra, and feature platforms.
• Identify and solve complex ML systems challenges across product areas, spanning model quality to serving latency.
• Develop extensible ML frameworks and engineering practices for consistency across teams.
• Lead cross-functional technical strategy for ML initiatives with multi-year roadmaps.
• Apply AI-native workflows to accelerate model development and evaluation pipelines.
• Define data-driven metrics linking model performance to business outcomes.
• Proactively identify risks in ML systems and partner with compliance on responsible AI.
• Mentor engineers on ML systems design, debugging, and production-grade AI.
• Drive performance improvements across training, data loading, serving, and hardware utilization.
• Influence the ML engineering community via publications, frameworks, and cross-industry engagement.

Skills

ML systems design

Production ML

Architectural leadership

Mentoring

Cross-functional collaboration

Model training pipelines

Inference infrastructure

Data integrity

Performance optimization

AI governance

Education

Bachelor's degree in Computer Science or related field

Job description

Meta is seeking a distinguished Software Engineer with deep machine learning expertise to drive transformative advances across Meta's AI-powered products and platforms. In this role, you will operate at the intersection of foundational ML research and large-scale production systems, shaping the technical direction of machine learning infrastructure, modeling, and applied AI across the organization. You will identify and solve the hardest ML systems challenges, define architectural standards, and leverage AI-native approaches to unlock step-change improvements in how Meta builds and deploys intelligent systems at global scale.

Software Engineer, Machine Learning Responsibilities:

• Define and own the technical architecture of critical machine learning systems, including model training pipelines, inference infrastructure, and feature engineering platforms, ensuring reliability and scalability across billions of users
• Identify and solve the most complex ML systems challenges across multiple product areas, including issues that span model quality, training efficiency, serving latency, and data integrity
• Develop and establish extensible ML frameworks, modeling standards, and engineering practices that drive consistency and velocity across multiple engineering organizations
• Lead cross-functional technical strategy for machine learning initiatives, aligning research, infrastructure, and product teams around multi-year roadmaps that balance short-term delivery with long-term architectural health
• Apply AI-native workflows and tooling as a force multiplier to accelerate model development cycles, automate evaluation pipelines, and expand the scope of what engineering teams can deliver
• Define new metrics and data-driven decision-making principles for long-term ML projects, connecting model performance signals to organization-level business outcomes
• Proactively identify systemic reliability, privacy, and integrity risks in ML systems and build robust technical safeguards, partnering with compliance and policy teams to ensure responsible AI deployment
• Mentor engineers across the organization on ML systems design, debugging complex model behavior, and building production-grade AI systems, establishing yourself as a sought-after technical coach and technical leader
• Drive performance improvements across large-scale ML systems by identifying bottlenecks that span training, data loading, model serving, and hardware utilization, and leading cross-org efforts to resolve them
• Influence the broader ML engineering community through technical publications, design frameworks, and cross-industry engagement that advances the field

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 12+ years of experience designing, building, and deploying large-scale machine learning systems in production environments
• Experience architecting end-to-end ML platforms spanning data pipelines, distributed training, model evaluation, and low-latency inference serving
• Experience identifying and resolving complex, cross-system ML failures including issues in model quality, training stability, feature consistency, and serving correctness
• Experience defining technical strategy and gaining organizational alignment across multiple engineering teams and cross-functional stakeholders
• Experience communicating complex ML system designs and trade-offs in writing to both technical and non-technical audiences, including executive leadership

Preferred Qualifications:

• Experience applying ML to multiple product domains such as ranking and recommendation, generative AI, computer vision, or natural language understanding
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Track record of industry-recognized contributions to machine learning systems, such as publications, open-source frameworks, or widely adopted architectural patterns
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience building AI-native developer tooling or automation that measurably accelerates ML experimentation and production deployment cycles
• Experience with large-scale foundation model training, fine-tuning, or inference optimization across distributed hardware clusters

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 Affinitive Action employer. 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].

$347,000/year to $403,000/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.