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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer - 2026 Vision

NexusAI Solutions
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
16 Mei 2026
Deadline
16 Mei 2027

Job Description

Join NexusAI Solutions at the forefront of technological innovation as we architect the intelligent systems of 2026. We're seeking a visionary AI/ML Engineer to transform cutting-edge research into scalable solutions that redefine industries. In this role, you'll collaborate with world-class teams to build autonomous systems, predictive models, and neural networks that shape tomorrow's digital landscape. If you're passionate about pushing the boundaries of artificial intelligence and want your work to impact billions of lives, this is your moment.

What We Offer:

Competitive equity package, unlimited learning stipend, flexible remote work options, and the opportunity to work on projects that will define the next decade of AI advancement. Our culture celebrates curiosity, experimentation, and bold thinking.

Responsibilities

  • Design and implement production-grade ML pipelines for autonomous systems and predictive analytics
  • Develop novel neural architectures for real-time decision-making platforms
  • Collaborate with quantum computing teams to optimize hybrid AI-quantum algorithms
  • Lead ethical AI framework development ensuring responsible deployment of advanced models
  • Create federated learning systems for cross-organizational data collaboration
  • Architect multimodal AI models processing text, vision, and sensor data simultaneously
  • Mentor junior engineers in emerging AI paradigms and best practices

Qualifications

  • 5+ years of ML engineering experience with production deployment of large-scale models
  • Expertise in TensorFlow/PyTorch and distributed training frameworks
  • Strong background in computer vision, NLP, and reinforcement learning
  • Proficiency in cloud-native ML deployment (AWS/GCP/Azure)
  • Publication record at NeurIPS/ICML/ICLR or equivalent industry impact
  • Experience with MLOps tools (MLflow, Kubeflow, Airflow)
  • Demonstrated ability to translate complex research into practical applications
  • PhD in ML/AI or equivalent industry breakthroughs

Required Skills

Python TensorFlow PyTorch Distributed Systems Computer Vision NLP Reinforcement Learning MLOps Quantum Computing Federated Learning

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