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AI/ML Engineer - Future Tech 2026

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join QuantumLeap Dynamics in pioneering the next frontier of artificial intelligence. We're seeking visionary AI/ML Engineers to architect solutions that will define 2026's technological landscape. This role offers unparalleled opportunities to shape emerging AI paradigms while working with industry-leading quantum computing infrastructure and neural network innovations.

Our cross-functional teams collaborate on autonomous systems, predictive analytics, and ethical AI frameworks that will transform industries worldwide. You'll develop scalable machine learning models, implement cutting-edge deep learning architectures, and contribute to patents that will shape the future of human-AI interaction.

Responsibilities

  • Design and deploy production-grade ML models for autonomous decision-making systems
  • Develop quantum-enhanced neural networks for next-gen AI applications
  • Implement ethical AI frameworks ensuring bias mitigation and transparency
  • Collaborate with quantum computing teams to optimize hybrid AI-quantum algorithms
  • Lead research initiatives in explainable AI and predictive analytics
  • Architect scalable AI infrastructure processing petabyte-scale datasets
  • Mentor junior engineers in emerging ML methodologies

Qualifications

  • MS/PhD in Computer Science, AI, or related field with 5+ years experience
  • Expertise in TensorFlow, PyTorch, and quantum ML frameworks (Qiskit, Cirq)
  • Proficiency in Python, R, and distributed computing frameworks
  • Published research in top-tier AI conferences (NeurIPS, ICML)
  • Experience deploying ML models on quantum hardware
  • Strong background in ethical AI development and bias mitigation
  • Certification in cloud AI platforms (AWS SageMaker, GCP Vertex AI)

Required Skills

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

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