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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Engineer

Nexus Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Are you ready to build the intelligence of tomorrow? Nexus Future Systems is seeking a visionary Senior AI Engineer to lead our next-generation research initiatives. In this pivotal role, you will architect scalable machine learning systems and deploy cutting-edge Large Language Models (LLMs) that redefine human-computer interaction. We are looking for a builder who is passionate about ethical AI and the technological frontier.


Join a team of world-class researchers and engineers dedicated to pushing the boundaries of what is possible in artificial intelligence. You will have the autonomy to experiment with novel architectures and the responsibility to ship production-grade models that impact millions of users worldwide.

Responsibilities

  • Design, train, and deploy state-of-the-art deep learning models to production environments.
  • Optimize inference latency and model performance for real-time AI applications.
  • Collaborate with product and engineering teams to integrate AI capabilities seamlessly into core products.
  • Mentor junior engineers and set technical standards for the AI research lab.
  • Research and implement novel algorithms for next-gen generative AI and autonomous agents.
  • Ensure data privacy, ethics, and compliance in all AI development processes.

Qualifications

  • PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of professional experience in machine learning engineering or research.
  • Expert proficiency in Python, PyTorch, and TensorFlow.
  • Deep understanding of NLP, LLMs, and RAG (Retrieval-Augmented Generation) architectures.
  • Strong experience with cloud platforms (AWS/GCP) and containerization (Docker/Kubernetes).

Required Skills

Python PyTorch TensorFlow Machine Learning NLP LLM AI Deep Learning Docker Kubernetes AWS GCP

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