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Senior AI Engineer (2026 Ready) - San Francisco, CA

Quantum Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
13 Mei 2026
Deadline
13 Mei 2027

Job Description

Quantum Horizon Labs is at the forefront of next-generation AI integration. We are seeking a visionary Senior AI Engineer to lead the architecture of our 2026 roadmap systems. If you are passionate about the future of generative AI, scalable infrastructure, and ethical machine learning, this is your opportunity to shape the digital landscape.

As a key member of our elite engineering team, you will bridge the gap between theoretical research and production-grade deployment, ensuring our solutions are robust, scalable, and ready for the demands of the 2026 market.

Responsibilities

  • Design and implement cutting-edge AI models and machine learning pipelines for large-scale applications.
  • Lead the architectural planning for our 2026 product roadmap, focusing on LLM optimization and real-time inference.
  • Collaborate with cross-functional teams (Product, Research, DevOps) to translate business requirements into technical solutions.
  • Optimize existing codebases for performance, scalability, and energy efficiency in cloud environments.
  • Conduct code reviews, mentor junior engineers, and foster a culture of continuous learning and innovation.
  • Stay ahead of emerging trends in AI, ensuring our stack remains future-proof.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
  • 5+ years of professional experience in Machine Learning, AI, or Deep Learning.
  • Proficiency in Python, TensorFlow, PyTorch, or JAX.
  • Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Experience with MLOps tools and data pipeline orchestration (Airflow, Spark).
  • Excellent problem-solving skills and the ability to work in a fast-paced, agile environment.

Required Skills

Python TensorFlow PyTorch Machine Learning AWS MLOps Deep Learning Docker Kubernetes

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