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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer (2026 Vision)

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join QuantumLeap Dynamics at the forefront of 2026's technological revolution. We're pioneering next-generation AI systems that will redefine human-machine interaction. As a key member of our elite R&D team, you'll architect transformative solutions in quantum computing integration, generative AI ethics, and neural network optimization. Enjoy unparalleled resources, flexible work arrangements, and stock options in a company valued at $2B+.

Our San Francisco campus offers state-of-the-art labs with direct access to quantum processors and GPU clusters. Collaborate with Nobel laureates and disrupt industries from healthcare to climate modeling. This is your chance to shape the future while enjoying Silicon Valley's premier compensation package.

Responsibilities

  • Design and implement scalable ML pipelines for real-time quantum data processing
  • Lead cross-functional teams in developing ethical AI frameworks for 2026 applications
  • Optimize neural architectures for quantum-accelerated training workflows
  • Architect generative AI systems with advanced multimodal capabilities
  • Pioneer new algorithms for federated learning across decentralized quantum networks
  • Drive innovation in explainable AI (XAI) for high-stakes decision systems
  • Collaborate with product teams to translate research into production-ready solutions

Qualifications

  • PhD or MS in Computer Science/AI with 5+ years of ML engineering experience
  • Expertise in PyTorch/TensorFlow and quantum computing frameworks (Qiskit, Cirq)
  • Proven track record deploying production-grade ML systems at scale
  • Deep knowledge of transformer architectures and diffusion models
  • Strong background in distributed computing and high-performance optimization
  • Published research in top-tier AI/ML conferences (NeurIPS, ICML, ICLR)
  • Experience with MLOps tools (MLflow, Kubeflow) and cloud platforms (AWS/GCP)

Required Skills

AI Machine Learning Quantum Computing PyTorch TensorFlow MLOps Neural Networks Generative AI Distributed Systems Python C++

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