Vagas remotas de Spark para candidatos em Estados Unidos.

High-touch white-glove onboarding

Design, build, and deploy production-grade machine learning models and systems at scale

Design and implement the orchestration layer that turns natural-language intent into reliable execution.

Discover and validate online signals from user interactions that serve as reliable proxies for true answer quality

Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases.

Define the architecture and contracts governing how models move from development to production — feature store design, model schema management, online/offline inference consistency, and multi-version support.

Define and drive the multi-year technical vision for Home and Cross-Retailer Search infrastructure, spanning retrieval, ranking, indexing, and personalization at scale.

Translate Instacart’s data strategy (e.g., monetization, federated access, real-time) into an actionable multi-year architecture roadmap; align with leadership while evolving the platform for scale, maturity, and cost efficiency.

Translate Instacart’s data strategy (e.g., monetization, federated access, real-time) into an actionable multi-year architecture roadmap; align with leadership while evolving the platform for scale, maturity, and cost efficiency.

Lead and break down complex problems while keeping the broader data vision in focus.

Lead research and development of pCTR and conversion prediction models, with a focus on improving calibration, reducing training data biases (selection bias, position bias, optimizer’s curse)

Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more

Relevance & recommendation systems (content, search, notifications)

7+ years of professional software engineering experience, with at least 3+ years focused on ML-driven systems at scale

Refine and maintain our data infrastructure technologies to support ML and analytics workflows on data collected from hundreds of millions of users.

Work with product managers to design and implement Ads products.

Work with product managers to design and implement Ads products.

Work with product managers to design and implement Ads products.

Lead the technical strategy, architecture, and implementation of Reddit’s next-generation ML Indexing & Retrieval engine, integrating capabilities across lexical and vector indexing, low-latency retrieval

Work with product managers to design and implement Ads products.

Design and build large-scale offline ML experimentation platforms that enable reproducible research, model development, evaluation, and promotion workflows.

Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more

Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities