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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer - Future Tech Visionary 2026

QuantumLeap Systems
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
18 Mei 2026
Deadline
18 Mei 2027

Job Description

Join QuantumLeap Systems at the forefront of technological evolution as we architect the intelligent infrastructure for 2026 and beyond. We're seeking visionary AI/ML Engineers to develop next-generation autonomous systems that will redefine industries. In this pivotal role, you'll collaborate with Nobel laureates and industry pioneers to transform theoretical breakthroughs into scalable solutions.

Our state-of-the-art San Francisco campus offers unparalleled resources including quantum computing labs and neural network testbeds. This is your opportunity to shape human-computer interaction paradigms and contribute to projects that will impact billions of lives.

Responsibilities

  • Design and implement cutting-edge AI/ML models for autonomous decision-making systems
  • Architect neural networks capable of predictive adaptation to emerging technological paradigms
  • Develop ethical frameworks for AI governance and bias mitigation in high-stakes environments
  • Create real-time learning systems that evolve with technological advancements
  • Collaborate with quantum computing teams to hybridize classical and quantum AI approaches
  • Lead R&D initiatives for human-AI symbiotic interfaces
  • Publish breakthrough research in top-tier AI conferences and journals

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years industry experience
  • Expertise in transformer architectures, reinforcement learning, and federated learning
  • Proven track record deploying production-grade ML systems at scale (>10M users)
  • Proficiency in PyTorch, TensorFlow, and distributed computing frameworks
  • Deep understanding of quantum machine learning principles
  • Published research in NeurIPS, ICML, or equivalent tier conferences
  • Experience with ethical AI frameworks and bias mitigation techniques
  • Ability to translate complex theoretical concepts into practical implementations

Required Skills

Machine Learning Deep Learning Neural Networks Python TensorFlow PyTorch Quantum Computing Reinforcement Learning NLP Computer Vision MLOps AI Ethics

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