Sr Lead AI Data Engineer
Overview
Lead design and delivery of AI infrastructure to drive scalable machine learning solutions across enterprise platforms. Own development of end-to-end ML pipelines and foster collaboration between data science and engineering teams. This role differs by focusing on cross-functional leadership and production-grade MLOps implementation.
What You'll Do9
- 1Design and implement high-performance ML pipelines using Python and PyTorch
- 2Architect and maintain distributed training frameworks leveraging TensorFlow and Hugging Face
- 3Establish CI/CD workflows for model deployment with Kubernetes orchestration
- 4Implement monitoring and observability solutions for production ML systems
- 5Mentor senior engineers and establish best practices for ML governance
- 6Scale inference services to support millions of daily active users
- 7Drive adoption of cloud-native architectures on AWS platforms
- 8Collaborate with product owners to define technical roadmaps for AI initiatives
- 9Optimize model training efficiency through hyperparameter tuning and hardware acceleration
Requirements7
- 15+ years experience building ML platforms with Spark and Airflow
- 24+ years leading MLOps initiatives for enterprise-scale applications
- 3Bachelor degree in Computer Science or related field
- 4Proficiency in Python and deep understanding of ML frameworks
- 5Strong background in distributed systems and containerization technologies
- 6Experience deploying models using Kubernetes and Docker
- 7Familiarity with AWS services and cloud architecture principles
Salary Insight
Salary not disclosed in listing
Location
Required Skills
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