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Information Technology 🏒 Full Time ⭐️ Verified

Senior Generative AI Engineer

Nexus Horizon AI
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

We are on the frontier of the AI Revolution. Nexus Horizon AI is seeking a visionary Senior Generative AI Engineer to architect and deploy the next generation of Large Language Models (LLMs) and multimodal systems. If you are passionate about pushing the boundaries of what is possible in machine learning and want to define the technological landscape of 2026, we want to meet you.

In this role, you will lead a high-impact team focused on building autonomous agents and generative workflows that transform complex data into actionable intelligence. Join us in building the future of artificial intelligence.

Responsibilities

  • Design, train, and fine-tune state-of-the-art generative models using Transformer architectures and diffusion techniques.
  • Optimize inference pipelines and model serving infrastructure for low-latency, high-throughput environments.
  • Collaborate with cross-functional teams of researchers and product engineers to integrate AI capabilities into consumer-facing applications.
  • Implement rigorous testing and validation frameworks to ensure model accuracy, safety, and robustness.
  • Conduct cutting-edge research to explore emerging trends in NLP, Computer Vision, and Reinforcement Learning.
  • Mentor junior engineers and contribute to the technical vision of the AI lab.

Qualifications

  • Master’s or PhD degree in Computer Science, Mathematics, or a related quantitative field.
  • 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
  • Extensive experience with deep learning frameworks (PyTorch, TensorFlow, or JAX).
  • Proven track record of deploying large-scale ML models in production environments.
  • Strong proficiency in Python, SQL, and distributed systems.
  • Experience with fine-tuning proprietary models (e.g., GPT-4, Llama 3) and building RAG (Retrieval-Augmented Generation) pipelines.

Required Skills

Python PyTorch TensorFlow NLP Large Language Models Machine Learning Deep Learning GPU Acceleration AWS Docker Kubernetes MLOps

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