Engineering Manager, Machine Learning

Meta; Menlo Park (CA); Presencial; USD 300.000 - 420.000; Jornada completa

Descripción de la vacante

Meta is seeking an Engineering Manager to lead machine learning engineering teams building state-of-the-art recommendation systems at scale. You will manage teams of ML engineers and technical leaders working on Meta Recommendation Systems (MRS) — from data pipelines and model development to training infrastructure and production deployment.

You will shape the technical strategy for recommendation and ranking initiatives, drive SOTA model adoption within your teams, and partner closely with

Formación

• 8+ years in software engineering with a focus on ML systems.
• 4+ years managing engineering teams including other leaders.
• Experience driving technical strategy and roadmap decisions for ML systems across the full model lifecycle.
• Experience partnering cross-functionally with product, data science, and research teams to define ML problem scope and deliver measurable outcomes.
• Experience recruiting, developing, and retaining ML engineering talent and building high-performing teams in ambiguous, high-impact areas.
• Track record of building recommendation systems that influenced product metrics at scale.
• Experience with state-of-the-art recommendation system architectures including deep learning, transformer-based models, and neural collaborative filtering.
• Experience with large-scale personalization systems, user modeling, and multi-objective ranking optimization.
• Demonstrated ability to integrate AI tools to optimize workflows and drive measurable impact.
• Demonstrated ability to adopt emerging techniques from top ML conferences into production systems.
• Experience implementing responsible AI practices (risk assessment, bias mitigation, quality checks).
• Track record of translating SOTA research into production recommendations.

Responsabilidades

• Lead ML engineers and technical leaders across data pipelines, model development, training, and deployment.
• Shape the technical strategy for recommendation and ranking initiatives across products.
• Drive adoption of state-of-the-art models within teams and align with product goals.
• Partner with product, data science, and research to deliver meaningful recommendation systems.
• Recruit, develop, and retain ML engineering talent and build high-performing teams in ambiguous, high-impact areas.

Conocimientos

ML leadership

Team management

ML systems

Model development

Training pipelines

Production ML infra

Cross-functional collaboration

Recommendation systems

Deep learning

Transformer models

Neural collaborative filtering

Personalization systems

Responsible AI

Herramientas

PyTorch

TensorFlow

Descripción del empleo

Meta is seeking an Engineering Manager to lead machine learning engineering teams building state-of-the-art recommendation systems at scale. In this role, you will manage teams of ML engineers and technical leaders working on Meta Recommendation Systems (MRS) — from data pipelines and model development to training infrastructure and production deployment. You will shape the technical strategy for recommendation and ranking initiatives, drive SOTA model adoption within your teams, and partner closely with product, data science, and research to deliver recommendation systems that have meaningful impact across Meta's products and platforms.

• 8+ years of experience in software engineering with a focus on machine learning systems, including model development, training pipelines, or ML infrastructure
• 4+ years of experience managing engineering teams, including experience managing other engineering leaders
• Experience driving technical strategy and roadmap decisions for ML systems across the full model lifecycle, from data ingestion through production serving
• Experience partnering cross-functionally with product, data science, and research teams to define ML problem scope and deliver measurable outcomes
• Experience recruiting, developing, and retaining ML engineering talent and building high-performing teams in ambiguous, high-impact areas
• Track record of building recommendation systems that directly influenced product metrics at significant scale
• Experience with state-of-the‑art recommendation system architectures including deep learning, transformer‑based models, and neural collaborative filtering
• Experience with large‑scale personalization systems, user modeling, and multi‑objective ranking optimization
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ability to evaluate and adopt emerging techniques from top ML conferences (RecSys, KDD, NeurIPS, ICML) into production systems
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Track record of implementing SOTA research papers into production recommendation and ranking systems
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience managing teams working on large‑scale recommendation, ranking, or retrieval systems in a production environment
• Hands‑on background in ML model development using frameworks such as PyTorch or TensorFlow, with specific experience in recommendation models