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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
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join QuantumLeap Labs at the forefront of technological evolution! We're seeking an AI/ML Engineer to architect breakthrough systems that will define 2026's digital landscape. As a pioneer in quantum-adjacent AI, you'll collaborate with Nobel laureates to develop next-gen neural networks and autonomous decision frameworks. Our state-of-the-art lab in San Francisco offers unparalleled resources to transform theoretical concepts into reality.

What You'll Achieve:

  • Deploy production-level AI systems serving 10M+ users
  • Lead research in quantum-enhanced machine learning
  • Shape industry standards for ethical AI deployment
  • Mentor the next generation of AI innovators

Responsibilities

  • Design and implement scalable ML pipelines for real-time data processing
  • Develop novel neural architectures for quantum-computing integration
  • Lead cross-functional teams in deploying AI solutions across industries
  • Research and publish breakthrough papers in top-tier AI conferences
  • Optimize algorithms for edge computing and IoT ecosystems
  • Architect ethical AI frameworks with built-in fairness and transparency
  • Collaborate with quantum physicists to hybridize classical and quantum ML

Qualifications

  • PhD in Computer Science/AI or equivalent with 5+ years industry experience
  • Expertise in PyTorch/TensorFlow and distributed ML systems
  • Proven track record of deploying production ML models serving >1M users
  • Publishing record in NeurIPS/ICML/ICLR or equivalent tier venues
  • Deep understanding of quantum computing principles and quantum algorithms
  • Experience with MLOps tools (Kubeflow, MLflow, BentoML)
  • Strong background in theoretical computer science and complexity theory
  • Portfolio demonstrating AI systems with measurable societal impact

Required Skills

Machine Learning Deep Learning Python TensorFlow PyTorch Quantum Computing MLOps Neural Networks AI Ethics Distributed Systems

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