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Lead AI/ML Engineer - 2026 Vision

QuantumLeap Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Join QuantumLeap Technologies at the forefront of 2026's technological revolution. We're seeking a visionary Lead AI/ML Engineer to architect and deploy next-generation artificial intelligence solutions that will redefine industries. You'll work in our state-of-the-art San Francisco hub, collaborating with Nobel Prize-winning researchers and Fortune 500 partners to build autonomous systems, predictive neural networks, and quantum-enhanced machine learning models.

This role offers unparalleled opportunities to shape humanity's technological trajectory with competitive equity, unlimited learning stipends, and a flexible hybrid work environment designed for peak innovation.

Responsibilities

  • Architect and implement cutting-edge AI/ML pipelines for autonomous systems and predictive analytics
  • Lead a team of 5+ engineers in developing quantum-enhanced machine learning models
  • Collaborate with product teams to translate business requirements into scalable AI solutions
  • Optimize deep learning models for edge deployment and real-time inference
  • Research and integrate emerging AI technologies (neuromorphic computing, federated learning)
  • Establish best practices for MLOps, model governance, and ethical AI frameworks
  • Present breakthrough findings at industry conferences and publish in top-tier journals

Qualifications

  • PhD in Computer Science, AI, or related field with 5+ years of industry experience
  • Expertise in PyTorch/TensorFlow and distributed training frameworks
  • Published research in top-tier AI/ML conferences (NeurIPS, ICML, CVPR)
  • Proven track record of deploying production-grade AI systems at scale
  • Strong background in quantum computing principles and quantum machine learning
  • Experience leading cross-functional teams through full AI project lifecycles
  • Proficiency in cloud platforms (AWS/GCP/Azure) and serverless architectures
  • Deep understanding of AI ethics, bias mitigation, and responsible AI practices

Required Skills

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

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