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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer - 2026 Visionary

QuantumLeap Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
25 Mei 2026
Deadline
25 Mei 2027

Job Description

Join QuantumLeap Technologies at the forefront of the 2026 technological revolution! We're seeking visionary AI/ML Engineers to architect intelligent systems that will redefine industries. Work in our state-of-the-art San Francisco lab alongside world-class researchers to develop autonomous AI solutions, quantum-enhanced machine learning models, and next-gen neural networks. Your innovations will power our flagship product suite serving 500M+ users globally. Enjoy unparalleled creative freedom, cutting-edge resources, and a culture that celebrates breakthrough thinking.

Responsibilities

  • Design and implement production-grade ML pipelines for real-time data processing at petabyte scale
  • Develop quantum-resistant AI algorithms for secure 2026-era applications
  • Lead neural architecture research for autonomous decision-making systems
  • Collaborate with cross-functional teams to integrate AI solutions into IoT ecosystems
  • Optimize models for edge computing deployment across distributed networks
  • Contribute to open-source frameworks that shape the future of AI
  • Mentor junior engineers in emerging ML paradigms

Qualifications

  • PhD or equivalent in Computer Science/AI with 5+ years industry experience
  • Expertise in transformer architectures, reinforcement learning, and federated learning
  • Proficiency in PyTorch, TensorFlow, and quantum computing frameworks
  • Published research in top-tier AI conferences (NeurIPS, ICML, ICLR)
  • Experience deploying ML models in production environments with 99.99% uptime
  • Strong background in distributed systems and high-performance computing
  • Demonstrated ability to translate complex technical concepts into business impact

Required Skills

AI/ML PyTorch TensorFlow Quantum Computing Neural Networks Reinforcement Learning Distributed Systems MLOps

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