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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Engineer

Nexus Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join Nexus Innovations at the forefront of 2026's technological revolution as a Senior AI Engineer. We're pioneering autonomous systems that will redefine industries, and we need visionary talent to architect the future. This role offers unparalleled opportunities to shape cutting-edge AI solutions while working alongside world-class researchers in our state-of-the-art San Francisco lab.

Our team operates at the intersection of quantum computing and neural networks, developing next-generation AI frameworks that will power the next decade of innovation. You'll lead initiatives to optimize machine learning pipelines, design ethical AI governance protocols, and mentor the next generation of AI pioneers. We offer competitive equity packages, unlimited learning stipends, and flexible hybrid work arrangements.

Responsibilities

  • Architect and deploy scalable AI/ML solutions for autonomous systems and predictive analytics
  • Lead research initiatives in quantum-enhanced neural networks and federated learning
  • Develop ethical AI governance frameworks aligned with 2026 regulatory standards
  • Mentor junior engineers and conduct technical workshops on advanced AI methodologies
  • Collaborate with cross-functional teams to integrate AI solutions into IoT and robotics platforms
  • Optimize computational efficiency for edge AI deployment across distributed networks
  • Stay current on emerging AI paradigms through continuous research and experimentation

Qualifications

  • MS/PhD in Computer Science, AI, or related field with 5+ years industry experience
  • Expertise in PyTorch, TensorFlow, and distributed ML frameworks
  • Strong background in reinforcement learning and generative adversarial networks
  • Proven track record deploying production-grade AI systems at scale
  • Familiarity with quantum computing principles and quantum machine learning
  • Experience with MLOps tools (Kubeflow, MLflow) and cloud platforms (AWS/GCP)
  • Published research in top-tier AI conferences or equivalent industry impact
  • Deep understanding of AI ethics and responsible AI development practices

Required Skills

Machine Learning PyTorch TensorFlow Quantum Computing Reinforcement Learning MLOps AI Ethics Distributed Systems

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