AI Engineering Technical Lead

🕒 Julho 18

🗽 New York – Remoto

🗽 New York – Remote

💵 $156.800 - $235.200 / ano

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

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Paramount

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1912

💼 Consultoria

📣 Marketing

📱 Mídia

Consulting • Marketing • Media

A Paramount é uma empresa global de entretenimento e notícias multimídia que oferece uma gama de serviços, incluindo assinatura digital direta ao consumidor via vídeo sob demanda e transmissão ao vivo através do Paramount+. Ela também é proprietária da Pluto TV, um serviço líder de televisão em streaming gratuito, MTV, a principal marca de entretenimento jovem do mundo, e CBS Sports, um líder em transmissões de esportes pela televisão. A Paramount Pictures, desde 1912, é uma produtora e distribuidora lendária de filmes, possuindo uma biblioteca de mais de 1. 000 títulos. A empresa é profundamente comprometida com inclusão e impacto, focando em diversidade, sustentabilidade global e conteúdo que promove mudanças. Sendo um jogador significativo em serviços de streaming ao vivo e sob demanda, a Paramount abrange uma ampla variedade de conteúdos, desde esportes até entretenimento infantil, comédia e documentários inovadores, impactando tanto plataformas lineares quanto de streaming globalmente.

Descrição

• Lead AI System Design & Development • Develop real-time and batch inference pipelines integrated with streaming data platforms. • Design feature engineering pipelines leveraging high-volume behavioral and content metadata. • Implement end-to-end ML workflows from data ingestion to model serving. • Build AI-Powered Data Products • Develop production-grade AI services that power user-facing and internal data products. • Design APIs and services to expose AI capabilities to downstream applications and platforms. • Ensure tight integration between AI systems and the core data platform. • Architect Scalable ML Infrastructure • Define architecture for model training, evaluation, deployment, and monitoring. • Build and optimize feature stores, model registries, and inference services. • Design systems that support low-latency, high-throughput model serving. • Establish best practices for reproducibility, versioning, and lifecycle management. • Production Reliability & Model Performance • Monitor and optimize model performance, latency, and system reliability in production. • Implement observability for data quality, feature drift, and model degradation. • Establish automated testing, validation, and deployment pipelines for ML systems. • Ensure scalability and cost efficiency across AI workloads. • Cross-Functional Collaboration • Partner with Data Engineers to integrate AI pipelines with real-time and batch data systems. • Collaborate with Product Managers to define AI-driven product capabilities and roadmap. • Work with Software Engineers to integrate AI services into user-facing applications. • Align with analytics and experimentation teams to measure model impact. • Technical Leadership • Lead architectural decisions for AI/ML systems and data-driven applications. • Mentor engineers in machine learning engineering, system design, and best practices. • Establish standards for model development, deployment, and operational excellence. • Drive innovation in applied AI across streaming and content platforms.

🎯 Requisitos

• Strong experience building and deploying machine learning models in production. • Expertise in recommendation systems, personalization, ranking models, or NLP. • Experience with model training frameworks (e.g., TensorFlow, PyTorch, or similar). • Understanding of feature engineering, model evaluation, and experimentation frameworks. • Experience designing large-scale feature pipelines using batch and streaming data. • Strong knowledge of data modeling and transformation for ML use cases. • Familiarity with feature stores and real-time feature serving architectures. • Experience integrating ML systems with real-time data platforms (e.g., Kafka, Pub/Sub). • Understanding of event-driven architectures and low-latency processing patterns. • Ability to design real-time inference and decisioning systems. • Strong experience with cloud-native architectures (GCP preferred). • Experience deploying ML systems in Kubernetes-based environments. • Understanding of distributed systems, scalability, and fault tolerance. • Proficiency in Python, Java, or similar languages for production systems. • Experience building microservices and APIs for model serving. • Strong software engineering fundamentals, including testing, CI/CD, and observability. • Strong foundation in machine learning engineering, data systems, and distributed architecture. • Proven track record of building and scaling AI/ML systems in production environments. • Experience working with real-time data platforms and high-scale user-facing systems. • Ability to balance long-term architecture with rapid product delivery. • Excellent leadership, problem-solving, and cross-functional collaboration skills. • Self-motivated, quality-driven, and focused on delivering measurable impact through AI.

🏖️ Benefícios

• medical • dental • vision • 401(k) plan • life insurance coverage • disability benefits • tuition assistance program • PTO