Autonomous Aircraft ML Engineer

SDFM; Rock Hill (SC); Presencial; USD 110.000 - 150.000; Jornada completa

Descripción de la vacante

Powerus is seeking a Machine Learning Engineer to build data, training, and deployment pipelines for models that run on its autonomous aircraft. You will curate datasets, implement reproducible training and evaluation workflows, and optimize models for on-board compute.

The role emphasizes delivering reliable models with verified latency and accuracy, managing model versions, and aligning with software release cycles in a defense/aerospace context.

Formación

• Bachelor's degree in CS/CE or related discipline or equivalent practical experience.
• Professional experience training and deploying machine learning models.
• Proficiency in Python and PyTorch or TensorFlow.
• Experience building data pipelines and managing large datasets.
• Experience with Linux, containers, and version control.
• U.S. Person status required; access to ITAR/EAR data.

Responsabilidades

• Build and maintain datasets from flight imagery and sensor logs, including labeling workflows and quality control.
• Develop training and evaluation pipelines with reproducible experiments and versioned data.
• Train, compress, and quantize models for embedded inference.
• Deploy models to aircraft compute and verify accuracy and latency on target hardware.
• Define evaluation metrics and test sets that reflect operational conditions.
• Track model versions and their association with software releases.

Conocimientos

Python

PyTorch

TensorFlow

Data pipelines

Model evaluation

Experiment tracking

Linux

Containers

Version control

Educación

Bachelor's degree in CS/CE or related

Herramientas

TensorRT

ONNX

MLflow

Weights & Biases

Descripción del empleo

Powerus is seeking a Machine Learning Engineer to build data, training, and deployment pipelines for models that run on its autonomous aircraft. You will curate datasets, implement reproducible training and evaluation workflows, and optimize models for on-board compute.

The role emphasizes delivering reliable models with verified latency and accuracy, managing model versions, and aligning with software release cycles in a defense/aerospace context.