Design and implement systems to collect and curate high-quality training datasets for supervised, unsupervised, and reinforcement learning use cases.
Build scalable featurization and preprocessing pipelines to transform raw data into structured inputs for AI/ML model development.
Partner with ML engineers and researchers to define data requirements and production workflows that support LLM-based agents and autonomous AI systems.
Lead the development of infrastructure that enables experimentation, evaluation, and deployment of machine learning models in production environments.
Support orchestration and real-time inference pipelines using Python and modern cloud-native tools, ensuring low-latency and high availability.
Mentor engineers and foster a high-performance, collaborative engineering culture grounded in technical excellence and curiosity.
Drive cross-functional alignment with product, infrastructure, and research stakeholders, ensuring clarity on progress, goals, and architecture.
Job Classification
Industry: InternetFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Technical ArchitectEmployement Type: Full time