ML Infrastructure Engineer: Data & Training Systems

PVH (Tommy Hilfiger/Calvin Klein); Costa Mesa (CA); On-site; USD 191,000 - 253,000; Full time

Benefits offered by this job

Equity grants

Comprehensive benefits

Job summary

Anduril Industries is seeking a Software Engineer for the ML Infrastructure team to build and operate core data management and model training systems for perception and autonomy use-cases. You’ll index multi-modal sensor data, orchestrate training across cloud and on-premise compute, and support deployment to edge devices.

You’ll contribute to frontier model integration, develop perception datasets, and enable observability across the ML lifecycle while partnering with perception engineers and

Qualifications

• Build and operate core training & dataset management infrastructure for perception engineers.
• Improve perception engineer-facing tooling & SDKs and iterate with users.
• Integrate frontier models for data augmentation, curation, and synthetic data generation.
• Enable observability & traceability across the ML lifecycle.
• Eagerly engage with customers to understand data requirements.

Responsibilities

• Develop core data management systems and model training orchestration across cloud/on-premise compute.
• Index and manage multi-modal sensor data for perception tasks.
• Train, evaluate, and deploy models to edge devices.
• Create tooling for monitoring training jobs and storing evaluation reports.
• Collaborate with customers and cross-functional teams to deliver solutions.

Skills

ML infrastructure

SDKs & tooling

Data augmentation

Observability

Customer engagement

Tools

Python

Rust

TensorFlow

PyTorch

Kubernetes

MLOps tooling

Dagster

Flyte

Airflow

Weights & Biases

MLFlow

Job description

Anduril Industries is seeking a Software Engineer for the ML Infrastructure team to build and operate core data management and model training systems for perception and autonomy use-cases. You’ll index multi-modal sensor data, orchestrate training across cloud and on-premise compute, and support deployment to edge devices.

You’ll contribute to frontier model integration, develop perception datasets, and enable observability across the ML lifecycle while partnering with perception engineers and