AI/ML Researcher
Dallas, TX | Remote
This position is the primary engine of discovery for Strike Global. As an AI/ML Researcher, you will be responsible for the mathematical and statistical foundations of our predictive engines. You will work on the frontier of high-frequency learning, identifying signals in high-dimensional, non-stationary data environments.
We are seeking a researcher with the intellectual depth to tackle non-trivial statistical challenges and the discipline to maintain objective rigor. You are not just analyzing data; you are architecting the Continuum.
Responsibilities
Signal Discovery: Conduct original research to identify non-linear signals in high-dimensional event streams. You will own the research cycle from initial hypothesis to validated mathematical proof.
Probabilistic Modeling: Design and refine sophisticated models to handle uncertainty and noise in real-time telemetry. You will develop recursive frameworks that adapt to shifting market topographies.
Backtesting Rigor: Architect high-fidelity simulation environments to validate strategies. You will ensure that models are resistant to overfitting and remain robust under extreme market pressure.
Cross-Functional Collaboration: Partner with technologists to ensure the seamless translation of mathematical theory into production-ready execution logic.
Literature Review: Stay at the forefront of academic and industrial research in deep learning, reinforcement learning, and information theory, integrating relevant breakthroughs into our sovereign stack.
Skills Required
Mathematical Mastery: Exceptional depth in stochastic processes, linear algebra, and information theory. A PhD in a quantitative field is preferred.
Scientific Python: Expert proficiency in the scientific Python stack (NumPy, SciPy, Pandas) and deep learning frameworks (PyTorch or JAX).
Statistical Intuition: A proven ability to find "Glint" in "noisy," unstructured data where traditional models fail.
Technical Precision: Familiarity with C++ and the ability to work within a low-latency environment.
Intellectual Autonomy: The ability to drive a research agenda independently. We value those who can identify the right questions, not just provide the answers.