Research Engineer III

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                        

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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