AI Engineering Technical Lead
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Job Description
AI Engineering Technical Lead developing intelligent systems for Paramount streaming platforms. Leading architectural decisions and mentoring engineers on AI/ML projects.
Responsibilities:
- 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.
Requirements:
- 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.
Benefits:
- medical
- dental
- vision
- 401(k) plan
- life insurance coverage
- disability benefits
- tuition assistance program
- PTO
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