Attis is a high-growth defense startup building next-generation situational awareness and telemetry platforms for critical defense infrastructure. They are seeking a Senior Machine Learning Engineer to architect, train, and optimize deep learning models from scratch, working with massive streams of unstructured time-series data in a fully remote environment.
Responsibilities:
- Architect, train, and optimize deep learning inference models entirely from scratch
- Process massive streams of unstructured time-series data (RF, audio waveforms, telemetry) in real-time
- Build a 'mixture of experts' inference architecture to balance speed and classification confidence
- Bypass managed cloud platforms to deploy robust models directly into custom Kubernetes infrastructure
- Work closely with data ingest teams to optimize hardware acceleration (CUDA) and low-level system performance
Requirements:
- U.S. Citizenship with the ability to obtain a U.S. Security Clearance
- Deep expertise in Python and deep learning frameworks (PyTorch preferred over TensorFlow)
- Proven history architecting models for high-velocity time-series or unstructured data
- Demonstrated ability to deploy models in non-managed, cloud-native environments (OCI, Docker, Kubernetes)
- Systems programming proficiency (C/C++) for extreme performance optimization of Python modules
- Previous experience operating within the defense sector, high-frequency trading, or critical infrastructure