Software Engineer - ML Infrastructure

Job description

Job requirements

• Build & operate our core model training & dataset management infrastructure : Perception engineers rely on reliable, high quality data to continually retrain and improve our detection & tracing systems.
• Improve perception engineer-facing tooling & SDKs: Perception engineers across Anduril rely on our core model training and evaluation framework.
• Integrate frontier models for data augmentation, curation, and synthetic data generation: While this team is not ultimately responsible for delivering perception systems for particular products, you will be responsible…
• Enable observability & traceability of the full ML lifecycle: You’ll build and develop systems that enable real-time monitoring of training jobs, tools to store/curate model evaluation reports, and our model registry.
• Eagerly engage with our customers : We partner closely with business line engineering teams to understand their specific data requirements and iteratively deliver solutions that meet their particular needs and…
• Strong proficiency in modern Python & exposure to Rust/the Rust ↔ Python toolchain (PyO3, Maturin, etc).
• Experience with modern deep learning frameworks such as Tensorflow or PyTorch, as well as distributed training paradigms
• Experience leveraging modern MLOps tooling on the orchestration side (Modal, Flyte, Airflow, Dagster, etc.), as well as common ML observability platforms (Weights & Biases, MLFlow, etc)