Applied AI Engineer
Core
Design, implement, and scale machine learning solutions for data quality assessment, automated validation, labeling, and intelligent data matching to power a trusted AI data platform.
Role type
Applied AI Engineer (ML Infrastructure & Data Quality)
Builds
ML models, data processing pipelines, and matching algorithms for AI training data
Domain
AI Infrastructure / Data Quality / Machine Learning
Deliverable
production ML models
Required skills
Machine Learning model development, Python, PyTorch, TensorFlow Serving, TorchServe, large-scale data processing, distributed computing, Docker, Kubernetes, Git, cloud services management
Preferred skills
Hugging Face, R, Scala, Master's or Ph.D. in Computer Science or Machine Learning
Technologies
PyTorch, TensorFlow Serving, TorchServe, Docker, Kubernetes, Git, Hugging Face, R, Scala
Responsibilities
Design and implement ML models for data quality and validation; Develop algorithms for automated data labeling and annotation verification; Create and maintain data processing pipelines; Develop and optimize matching algorithms; Implement scalable solutions for large datasets; Research and implement state-of-the-art ML techniques
Seniority
Individual Contributor, early-stage team member
