Senior Machine Learning Engineer (Signals & Systems)

Attis is a high-growth defense technology startup seeking a Senior Machine Learning Engineer specializing in Signals & Systems. The role involves architecting custom neural layers and optimizing models for real-time signal processing in a mission-critical environment.

Responsibilities:

• Designing Model Internals: Architecting custom neural layers, loss functions, and optimization strategies for high-frequency time-series data
• Applying SOTA Research: Implementing Transformers for time-series, Self-Supervised Representation Learning (SSL), and Joint-Embedding Predictive Architectures (JEPA) on unlabeled sensor streams
• Low-Level Optimization: Using C++ and CUDA to optimize your own inference plane. The environment is bare-metal and air-gapped Kubernetes; your code must be modular, hardened, and 'plug-and-play.'
• Rigorous Validation: Building evaluation frameworks for extreme class imbalance (identifying the 0.01% anomaly in MHz/GHz noise)

Requirements:

• 7+ years of professional industry experience specifically modeling physical signals (RF, Radar, Sonar, Acoustics, or high-fidelity Aerospace telemetry). General software engineering or generic data science years do not count toward this floor
• Deep expertise in PyTorch for designing and training custom deep learning architectures from scratch
• A deep academic and practical grasp of Information Theory, Entropy, and Stochastic Processes (ideally a PhD/MS in Physics, EE, or Applied Math)
• Mastery of C++ or Rust for performance-critical code. You must be able to bypass Python bottlenecks to hit real-time processing goals
• You are technically opinionated and ready to lead technical debates. This culture values rigorous argument over corporate bureaucracy