Software Engineer, Core Machine Learning

Meta • Sunnyvale, CA • 5h ago

Summary:

Meta is seeking a Staff Software Engineer to join the Core Machine Learning team, focused on building and scaling the foundational ML infrastructure and systems that power Meta's family of products. In this role, you will architect and deliver high-impact ML platform capabilities - spanning training infrastructure, model serving, feature engineering pipelines, and AI-accelerated developer tooling - that enable thousands of engineers and researchers across Meta to build and ship state-of-the-art machine learning models at scale.

Required Skills:

Software Engineer, Core Machine Learning Responsibilities:

Architect and own large-scale ML infrastructure systems, including distributed training frameworks, model serving platforms, and feature computation pipelines that support production workloads across Meta's product surface

Lead the technical design and implementation of foundational ML platform components, evaluating trade-offs across performance, reliability, and developer experience

Drive end-to-end delivery of major ML infrastructure initiatives, coordinating across teams and disciplines to align on priorities, manage dependencies, and execute phased rollouts

Identify and resolve performance bottlenecks in ML training and inference systems through instrumentation, profiling, and targeted optimization

Define and enforce service level objectives for core ML platform services, building dashboards, alerting systems, and runbooks to reduce mean time to mitigation during incidents

Establish and advocate for engineering best practices in ML systems development, including testing strategies, safe rollout patterns, and AI-accelerated development workflows

Collaborate with research, product engineering, and infrastructure teams as a credible technical co-owner, independently driving design reviews, data analyses, and architectural decisions

Mentor other engineers on ML systems design, debugging complex distributed system issues, and applying AI tools to accelerate development velocity

Contribute to the team's technical roadmap by identifying opportunities to improve ML platform capabilities and obtaining buy-in from key stakeholders across the organization

Minimum Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

8+ years of experience in software engineering with a focus on machine learning systems, ML infrastructure, or large-scale distributed systems

Experience designing and implementing production ML systems such as distributed training frameworks, model serving infrastructure, or large-scale feature engineering pipelines

Experience leading major technical initiatives from design through production, including cross-team coordination and phased rollout management

Experience with performance analysis and optimization of ML training or inference workloads, including profiling, instrumentation, and bottleneck resolution

Experience communicating technical decisions and trade-offs in writing to both engineering and non-engineering stakeholders through design documents, architectural proposals, or postmortems

Preferred Qualifications:

Experience defining and operating ML platform reliability programs, including resiliency testing, SLO frameworks, and incident retrospective processes

Experience building or contributing to open-source ML frameworks or platform tooling such as PyTorch, TensorFlow, Ray, or similar systems

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)

Experience applying AI-assisted development tools to accelerate engineering workflows, including code generation, automated testing, or intelligent debugging

Experience with hardware-software co-design for ML workloads, including quantization, model compression, or resource-efficient AI techniques

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

Public Compensation:

$183,997/year to $257,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative 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 stereo@types, 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 accommodations-ext@meta.com.

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