AI Engineering Lead — Real-Time Personalization

Paramount Pictures; Burbank (CA); On-site; USD 156,800 - 235,200; Full time

Benefits offered by this job

Benefits package

Paid time off

On-site and virtual engagement events

Job summary

Paramount Pictures is seeking an AI Engineering Technical Lead to drive design, development, and productionization of AI-powered data products across Paramount streaming platforms. You will lead intelligent systems for real-time and batch data, powering personalization, recommendations, content discovery, and analytics.

In this role, you will define architecture, mentor engineers, and ensure production-grade performance, scalability, and reliability of AI-driven systems, while collaborating with

Qualifications

• 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.

Responsibilities

• Lead real-time and batch inference pipelines integrated with streaming data platforms.
• Develop production-grade AI services powering user-facing and internal data products.
• Define architecture for model training, evaluation, deployment, and monitoring.
• Collaborate with Data Engineers and Product Managers to define AI-driven capabilities and roadmaps.
• Establish standards for model development, deployment, and operational excellence.

Skills

Machine learning in production

Recommendation/personalization

Model serving APIs

Python/Java

CI/CD & observability

Tools

TensorFlow

PyTorch

Kafka

Kubernetes

Feature stores

Job description

Paramount Pictures is seeking an AI Engineering Technical Lead to drive design, development, and productionization of AI-powered data products across Paramount streaming platforms. You will lead intelligent systems for real-time and batch data, powering personalization, recommendations, content discovery, and analytics.

In this role, you will define architecture, mentor engineers, and ensure production-grade performance, scalability, and reliability of AI-driven systems, while collaborating with