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

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