Description

“Help shape the mathematical core of next-generation intelligent systems — from strategic vision to edge execution.”

Location: Remote / Hybrid / On-site (flexible based on candidate profile)

Security Clearance:  Eligibility Preferred

Employment Type: Full-Time / Contract-Based (initial 12–18 months, with extension options)

 

About the Role

We are looking for an exceptional Applied Mathematician to lead the algorithmic design of a groundbreaking AI system focused on image recognition and intelligent reasoning for military applications. This role is critical to the development of a next-generation AI framework based on successive approximation, heuristics, and computational geometry, enabling real-time decision-making in mission-critical environments.

You will work closely with AI/ML engineers, system architects, and infrastructure specialists to convert theoretical models into operational capabilities for perception systems, situational awareness, trajectory modeling, sensor fusion, and autonomous behaviors.

 

 

Key Responsibilities

  • Design novel algorithms grounded in successive approximation, numerical analysis, and iterative convergence.
  • Apply computational geometry, discrete optimization, and probabilistic reasoning to enhance computer vision and AI reasoning pipelines.
  • Define and formalize convergence strategies, heuristic frameworks, and evaluation metrics tailored to specific military scenarios (e.g., object detection, trajectory generation, RF/thermal fusion).
  • Collaborate with AI/ML engineers to integrate mathematical models into machine learning workflows and inference systems.
  • Develop simulation environments to test and refine mathematical models under uncertainty, noise, and adversarial conditions.
  • Provide mathematical oversight for AI systems operating on edge devices, UAVs, satellite imaging platforms, and real-time targeting systems.
  • Document mathematical theory, modeling assumptions, and architectural blueprints for research continuity and IP protection.

 

 

Required Qualifications

  • PhD in Mathematics, Applied Mathematics, Computational Mathematics, or equivalent field.
  • 5+ years of experience applying mathematics in AI, defense, simulation, or high-performance computing systems.
  • Deep understanding of:
  • Successive approximation, fixed-point theory, and error convergence
  • Optimization theory and discrete math
  • Computational geometry, matrix algebra, and vector space transformations
  • Probabilistic models (e.g., Bayesian inference, MCMC, statistical learning)
  • Proficiency in mathematical programming tools such as Python (NumPy, SciPy), MATLAB, Mathematica, or Julia.

 

 

Preferred Qualifications

  • Experience in AI/ML algorithm design (e.g., custom loss functions, optimization kernels).
  • Familiarity with computer vision algorithms and geometric modeling for:
  • Object detection and classification
  • SLAM, spatial segmentation, 3D modeling
  • Exposure to reinforcement learning or heuristic-guided search models.
  • Knowledge of adversarial reasoning, anomaly detection, and signal processing for real-time inference systems.
  • Publications, patents, or peer-reviewed contributions in applied mathematics or AI modeling.
  • Understanding of security-sensitive environments and military-grade system constraints.

 

 

What We Offer

  • Opportunity to work on cutting-edge national security and defense AI initiatives.
  • A founding-level position with architectural and scientific influence.
  • Competitive compensation and flexible work structure.
  • Collaboration with an elite, multidisciplinary team across AI, defense tech, and R&D.
  • Potential for long-term leadership in building a modular AI platform applicable to defense, aerospace, and critical infrastructure.

 

 

Application Instructions

Please send the following materials to [jobs@visionwave.com]:

  • CV or Resume (with publication list if applicable)
  • Statement of interest (1–2 paragraphs on your mathematical background and how it aligns with defense AI challenges)
  • (Optional) Samples of mathematical models, publications, or code