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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer (2026 Visionary)

QuantumLeap Technologies
Austin
Estimated Salary
USD 180.000 – USD 280.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Join QuantumLeap Technologies at the forefront of innovation shaping 2026's technological landscape. We're seeking a visionary AI/ML Engineer to develop next-generation solutions that will redefine industries. Our Austin-based team operates at the intersection of quantum computing and machine intelligence, creating systems that solve previously impossible challenges. This role offers unparalleled opportunities to work on cutting-edge projects with industry pioneers while enjoying Austin's dynamic tech ecosystem. We provide comprehensive benefits, flexible work arrangements, and a culture that celebrates bold thinking.

Responsibilities

  • Design and implement scalable AI/ML models using TensorFlow, PyTorch, and quantum-inspired algorithms
  • Lead research initiatives for 2026-era autonomous systems and predictive analytics platforms
  • Collaborate with cross-functional teams to integrate AI solutions into quantum computing frameworks
  • Optimize model performance for edge computing and distributed quantum networks
  • Develop ethical AI governance frameworks aligned with 2026 regulatory standards
  • Mentor junior engineers and contribute to open-source quantum-ML projects

Qualifications

  • MS/PhD in Computer Science, AI, or related field with 5+ years industry experience
  • Expertise in Python, quantum machine learning libraries, and high-performance computing
  • Proven track record deploying production-grade ML systems at scale
  • Deep understanding of quantum computing principles and their ML applications
  • Strong background in distributed systems and cloud-native architectures (AWS/GCP/Azure)
  • Published research in top-tier AI/quantum conferences (NeurIPS, QIP)
  • Experience with MLOps and automated ML pipeline development

Required Skills

Python TensorFlow PyTorch Quantum Computing Machine Learning AWS MLOps Distributed Systems AI Ethics

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