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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer - 2026 Visionary

QuantumLeap Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027

Job Description

Join QuantumLeap Labs at the forefront of technological evolution for 2026. We're seeking visionary AI/ML engineers to architect next-generation autonomous systems that will redefine industries. Our cutting-edge research lab offers unparalleled resources to transform theoretical concepts into breakthrough applications. Collaborate with Nobel laureates and pioneer solutions in quantum computing, neural networks, and predictive analytics. Enjoy flexible work arrangements, unlimited learning stipends, and equity in our rapidly scaling unicorn.

Responsibilities

  • Design and deploy scalable ML pipelines for real-time autonomous decision-making systems
  • Pioneer quantum-ML hybrid algorithms to solve previously unsolvable computational challenges
  • Lead cross-functional teams in prototyping 2026-era AI applications (e.g., AGI frameworks, neuromorphic computing)
  • Optimize neural architectures for edge deployment in next-gen IoT ecosystems
  • Develop ethical AI governance frameworks aligned with 2026 regulatory landscapes
  • Drive open-source contributions to accelerate global AI progress

Qualifications

  • PhD or equivalent in Computer Science/AI with 5+ years of ML engineering experience
  • Expertise in PyTorch/TensorFlow and quantum computing frameworks (Qiskit, Cirq)
  • Published research in top-tier AI conferences (NeurIPS, ICML) or equivalent industry impact
  • Proven track record of deploying production ML systems at scale (>10M users)
  • Deep understanding of transformer architectures and emerging AI paradigms
  • Experience with neuromorphic hardware and quantum machine learning
  • Strong background in AI ethics and regulatory compliance frameworks

Required Skills

Machine Learning Deep Learning Quantum Computing Neural Networks PyTorch TensorFlow AI Ethics Quantum ML Neuromorphic Computing AGI Reinforcement Learning

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