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Senior AI/ML Engineer - Architecting the 2026 Vision

Nexus Horizon
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Lead the AI Revolution at Nexus Horizon

We are not just looking for engineers; we are looking for visionaries. Nexus Horizon is at the forefront of the Generative AI boom, and we are seeking a Senior AI/ML Engineer to join our elite team in San Francisco.

As we approach the transformative era of 2026, our mission is to build the next generation of Artificial General Intelligence (AGI) infrastructure. You will work on large-scale language models, optimize inference pipelines, and deploy AI solutions that redefine industry standards. If you are passionate about pushing the boundaries of what is possible with Deep Learning and NLP, this is your opportunity to shape the future.

Why join us?

  • Work on projects that have a direct impact on billions of users.
  • Competitive equity package and top-tier benefits.
  • Work in a state-of-the-art facility in the heart of SF.

Responsibilities

  • Design, train, and fine-tune state-of-the-art Large Language Models (LLMs) using PyTorch and TensorFlow.
  • Optimize model inference performance and reduce latency for real-time applications.
  • Build and maintain robust MLOps pipelines for continuous training and deployment.
  • Collaborate with cross-functional teams of researchers, product managers, and engineers to define product requirements.
  • Conduct rigorous testing and validation to ensure model accuracy, safety, and ethical alignment.
  • Stay ahead of the curve by researching the latest advancements in AI research papers and integrating them into our stack.

Qualifications

  • Master’s or PhD in Computer Science, Statistics, or a related field with a focus on AI/ML.
  • 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
  • Expert proficiency in Python, including experience with libraries such as NumPy, Pandas, and Scikit-learn.
  • Strong understanding of transformer architectures, attention mechanisms, and LLM fine-tuning techniques.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
  • Proven track record of shipping production-ready AI models.

Required Skills

Python PyTorch TensorFlow LLMs NLP Deep Learning MLOps AWS Docker Kubernetes

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