AI/ML Research Engineer
4 days ago
About Us
Auric AI builds AI-first products exclusively for defense and intelligence applications. We're a self-funded, research-driven company working on unprecedented technical challenges that compete with the best in the world. Small team people), 3-4 year runway, zero commercial pressure and pure focus on technical excellence.
The Role
You'll architect and build novel AI/ML systems for multi-modal intelligence analysis at scale. This involves designing new approaches for:
- Cross-modal data fusion and correlation across heterogeneous sources
- Geospatial-temporal reasoning and pattern discovery
- Query understanding and semantic search for specialized domains
- Anomaly detection in sparse, adversarial environments
- Real-time inference at scale with strict latency requirements
This is NOT:
- Applying existing frameworks to new datasets
- Fine-tuning foundation models
- Standard RAG/retrieval systems
- Incremental optimization work
This IS:
- Designing novel architectures from first principles
- Research that gets deployed to production within months
- Direct user interaction with military/intelligence analysts
- Building systems where failure has real-world consequences
What You Have
1. Exceptional First Principles Thinking
- You decompose complex problems to fundamentals and build novel solutions from scratch
- You do not respect arbitrary convention
2. Deep Algorithmic Foundations
Beyond ML, you have mastery in:
- Spatial algorithms: R-trees, k-d trees, geometric algorithms
- Graph algorithms: temporal graphs, probabilistic graphical models
- Temporal reasoning: causal inference, time-series analysis
- Optimization: combinatorial optimization, approximate algorithms
3. Novel Architecture Design
You've built systems that don't fit existing frameworks:
- Published novel architectures or deployed unprecedented systems
- Created domain-specific neural network components
What You Get
Technical Freedom:
- No project managers, no arbitrary deadlines
- You define what to build based on user needs
- Full ownership: problem definition to deployment
- Accept 70% failure rate in research
Environment:
- Work with researchers from top institutions
- Access to cutting-edge compute and specialized datasets
- Direct access to end users for rapid iteration
- Culture of intellectual honesty, zero politics
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