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Information Technology 🏒 Full Time ⭐️ Verified

AI/ML Engineer - Future-Tech Innovator

Nexus Horizon
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Are you ready to define the technological landscape of 2026? Nexus Horizon is seeking a visionary AI/ML Engineer to spearhead our next generation of intelligent systems. In this pivotal role, you won't just build models; you will architect the future of human-machine interaction. Join a elite team dedicated to pushing the boundaries of artificial intelligence, ethics, and scalability.

We are looking for a problem-solver who thrives in ambiguity and is passionate about the next wave of technological evolution. If you are ready to lead the charge in the AI revolution, this is your opportunity.

Responsibilities

  • Design, develop, and deploy state-of-the-art machine learning models and algorithms.
  • Build scalable AI infrastructure that supports high-volume data processing and real-time inference.
  • Collaborate with product managers and engineers to translate business requirements into technical AI solutions.
  • Conduct rigorous experimentation and A/B testing to optimize model performance and accuracy.
  • Ensure AI systems adhere to ethical guidelines, bias mitigation standards, and data privacy regulations.
  • Mentor junior engineers and contribute to the technical roadmap for future AI capabilities.

Qualifications

  • Master’s degree in Computer Science, Mathematics, Statistics, or a related field (PhD preferred).
  • 5+ years of professional experience in Machine Learning Engineering or Data Science.
  • Proficiency in programming languages such as Python, Java, or C++.
  • Strong expertise in ML frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Proven track record of deploying models to production environments.

Required Skills

Python TensorFlow PyTorch Machine Learning Deep Learning Cloud Computing AWS Docker Kubernetes Data Structures Algorithms

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