Research Engineer III

Team: Applied Machine Learning

Location: US - Remote

Commitment: Intern - Paid

Workplace Type: remote

Join our team building production ML infrastructure for enterprise-scale machine learning pipelines.You'll work on a platform that orchestrates end-to-end ML workflows from data ingestion through model training,  evaluation, and deployment.

How will you contribute?

• Build and maintain Apache Airflow DAGs for ML pipeline orchestration            
• Develop SageMaker training jobs for NLP models (NeMo, PyTorch)
•  Implement MLflow tracking and model registry integrations                       
•  Write infrastructure-as-code using Terraform (AWS S3, IAM, VPC)                 
•  Create comprehensive tests for ML pipeline components                           
• Follow spec-driven development practices with Claude Code             
•  Contribute to ML observability and evaluation frameworks                        

What will you bring?

• Experience with PyTorch, transformers, or other ML libraries                         
• Familiarity with ML model evaluation and experimentation                        
•  Interest in ML/AI infrastructure and operations
•  Strong problem-solving and debugging skills                                     
• Comfortable with Linux/command-line environments                                                                                      
• Knowledge of AWS services (S3, SageMaker, IAM)                                 
• Exposure to Apache Airflow or workflow orchestration                            
• Understanding of CI/CD, testing, or infrastructure-as-code