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Senior AI/ML Engineer 2026 - Future Tech

Nexus Horizon AI
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027

Job Description

Welcome to the future of intelligent systems. Nexus Horizon AI is pioneering the next generation of artificial intelligence, and we are seeking a visionary Senior AI/ML Engineer 2026 to join our elite engineering team. If you are passionate about shaping the technological landscape of tomorrow, this is your opportunity to lead high-impact projects that define the future.

In this role, you will work on cutting-edge Generative AI, Large Language Models (LLMs), and autonomous systems. You will bridge the gap between theoretical research and production-scale deployment, ensuring our solutions are scalable, ethical, and transformative.

Responsibilities

  • Architect and deploy scalable machine learning pipelines for Generative AI applications.
  • Research and implement state-of-the-art algorithms to improve model accuracy and efficiency.
  • Collaborate with cross-functional teams including data scientists, product managers, and engineers to define product requirements.
  • Optimize existing models for reduced latency and lower computational costs.
  • Mentor junior engineers and contribute to the technical roadmap for 2026 and beyond.
  • Ensure robust data governance, privacy compliance, and ethical AI practices.

Qualifications

  • 5+ years of experience in machine learning, deep learning, or natural language processing.
  • Strong proficiency in Python, TensorFlow, PyTorch, and C++.
  • Proven track record of deploying LLMs and Transformer architectures in production environments.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Master’s degree or PhD in Computer Science, Mathematics, or a related field.
  • Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python TensorFlow PyTorch NLP LLMs Machine Learning Deep Learning AWS Docker Kubernetes MLOps

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