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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer

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

Job Description

Join QuantumLeap Technologies at the forefront of 2026's technological revolution! We're seeking visionary AI/ML Engineers to architect intelligent systems that will redefine industries. As a key innovator in our San Francisco hub, you'll collaborate with Nobel laureates and disrupt industry paradigms using quantum-enhanced machine learning.

Our cutting-edge lab offers unparalleled resources to develop ethical AI frameworks, deploy next-gen neural networks, and pioneer solutions for climate modeling, personalized medicine, and autonomous systems. This is your chance to shape humanity's digital future while working in a culture that celebrates intellectual curiosity and audacious innovation.

Responsibilities

  • Design and implement quantum-optimized machine learning architectures for real-time data processing
  • Lead cross-functional teams in developing ethical AI frameworks for regulated industries
  • Develop predictive models for climate science and personalized healthcare applications
  • Architect scalable ML pipelines processing petabytes of multimodal data
  • Pioneer federated learning systems for privacy-preserving AI deployment
  • Mentor junior engineers in quantum computing principles and advanced ML techniques
  • Collaborate with product teams to translate AI capabilities into market-ready solutions

Qualifications

  • PhD in Machine Learning, Quantum Computing, or related field with 5+ years industry experience
  • Expertise in Python, TensorFlow/PyTorch, and quantum programming frameworks (Qiskit, Cirq)
  • Proven track record deploying production ML systems processing >10TB data daily
  • Published research in top-tier AI/ML conferences (NeurIPS, ICML, ICLR)
  • Deep understanding of quantum algorithms for ML acceleration
  • Certification in cloud ML platforms (AWS SageMaker, Azure ML) and MLOps best practices
  • Experience with federated learning and differential privacy frameworks
  • Demonstrated ability to translate complex technical concepts to executive stakeholders

Required Skills

Machine Learning Quantum Computing TensorFlow PyTorch Python AWS SageMaker Azure ML Qiskit Cirq Federated Learning MLOps Data Science

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