Machine Learning Engineer, Senior

9 Mothers Defense develops AI-enabled systems to counter unmanned aerial threats. Our first product, EDDA, is an autonomous counter-sUAS point-defense platform designed to detect, track, and neutralize Group 1 drone threats. The company is headquartered in Austin, Texas.

9 Mothers is seeking a Machine Learning Engineer to design, train, and maintain the models that power our counter-sUAS perception stack. The Machine Learning Engineer is responsible for model research, dataset engineering, and the training infrastructure that supports detection, classification, and discrimination of aerial targets. This is an individual contributor position.

We don’t use RAG, LLMs, or pre-built cloud APIs. Our stack requires building from the ground up to solve high-stakes problems under strict Size, Weight, and Power (SWaP) constraints. You should be capable of building models from scratch and have a fundamental understanding of the problem space.

• Design, train, and iterate on machine learning models for detection, classification, and tracking of aerial targets.

• Own the dataset pipeline end-to-end, including data collection, labeling, curation, augmentation, synthetic data generation, and closed-loop retraining based on field performance.

• Build and maintain training infrastructure, including experiment tracking, compute orchestration, and evaluation harnesses.

• Define metrics and evaluation methodologies that correlate to real-world operational performance.

• Support deployment of trained models into the production perception stack, and address discrepancies between training and deployed performance.

• Analyze field data to identify and address model failure modes.

• Demonstrated experience shipping machine learning systems into production under real-world operational requirements.

• Fluency in PyTorch or JAX, including full training loop development beyond fine-tuning off-the-shelf models.

• Strong software engineering skills beyond model development, including ownership of training infrastructure.

• Proficiency in Python; working knowledge of C++ or Rust at the training-to-deployment boundary.

• U.S. citizenship and ability to pass a background check.

• Experience with detection or tracking of small, fast, or adversarially perturbed targets.

• Synthetic data generation and sim-to-real methodologies.

• Experience training models for edge deployment, including quantization-aware training and knowledge distillation.

• Prior experience in defense or other safety-critical machine learning applications.

• Active security clearance, or eligibility to obtain one.

• Passion for building robots or engineering projects as a hobby

1. Application screen phone call (30 min)

2. Live coding test with the Director of Engineering (45 min via MS Teams)

3. Paid take-home consulting agreement ($500, ~4-8 hours)

6. Onsite interview in Austin

7. Offer

9 Mothers is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

This position may require access to information or technology subject to U.S. export control laws and regulations, including the International Traffic in Arms Regulations (ITAR). U.S. citizenship is required.