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AI Research Scientist - 2026 Innovation Lab

QuantumLeap Dynamics
Austin
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join QuantumLeap Dynamics at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. Our Austin-based Innovation Lab seeks visionary AI Research Scientists to develop next-generation neural networks and autonomous systems that will redefine human-machine interaction. This role offers unparalleled opportunities to collaborate with Nobel laureates and industry disruptors while working in a state-of-the-art facility equipped with quantum computing infrastructure.

We provide comprehensive benefits including equity grants, flexible hybrid work arrangements, and dedicated R&D budgets for personal projects. Our culture emphasizes intellectual curiosity and rapid prototyping in an environment where 80% of your time is dedicated to high-impact research.

Responsibilities

  • Design and implement novel deep learning architectures for 2026-era autonomous systems
  • Lead cross-functional research initiatives integrating quantum computing with classical AI
  • Publish breakthrough findings in top-tier journals (NeurIPS, ICML) and industry whitepapers
  • Develop ethical frameworks for AI deployment in regulated industries
  • Prototype and validate solutions in our 5G/6G testbed environment
  • Mentor junior researchers and collaborate with academic partners

Qualifications

  • PhD in Computer Science, Machine Learning, or related field (or equivalent experience)
  • 5+ years of experience in neural network research with proven publications
  • Expertise in Python, TensorFlow/PyTorch, and distributed computing frameworks
  • Strong background in reinforcement learning or federated learning
  • Experience with quantum computing APIs (Qiskit, Cirq) preferred
  • Portfolio of deployed AI systems handling >10M daily transactions
  • Authorization to work in the United States without sponsorship

Required Skills

AI Research Machine Learning Deep Learning Python TensorFlow Quantum Computing Neural Networks Reinforcement Learning Distributed Systems Ethics in AI

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