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Senior AI/ML Engineer

Nexus AI Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

We are seeking a visionary Senior AI/ML Engineer to join our elite team in San Francisco. As a leader in the generative AI space, Nexus AI Systems is building the next generation of autonomous intelligent agents. In this role, you will design and deploy scalable machine learning architectures that power our core products, working alongside world-class researchers and engineers.

You will be responsible for the full lifecycle of AI model development—from research and training to production deployment and optimization. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and Deep Learning, we want to hear from you.

Responsibilities

  • Design, train, and fine-tune state-of-the-art deep learning models, including LLMs and transformers.
  • Architect and implement robust MLOps pipelines for continuous integration and deployment of AI models.
  • Optimize model inference latency and reduce computational costs for large-scale production environments.
  • Collaborate with cross-functional teams (Product, Engineering, Data Science) to translate business requirements into technical AI solutions.
  • Conduct cutting-edge research to stay ahead of industry trends in artificial intelligence and machine learning.
  • Review and debug complex codebases, ensuring high code quality and adherence to best practices.

Qualifications

  • PhD or Master’s degree in Computer Science, Mathematics, Physics, or a related field, with a focus on AI/ML.
  • 5+ years of professional experience in machine learning engineering, deep learning, or data science.
  • Strong proficiency in Python, PyTorch, and TensorFlow.
  • Extensive experience with distributed training frameworks (e.g., Ray, Spark MLlib) and cloud platforms (AWS, GCP, or Azure).
  • Proven track record of deploying machine learning models into production environments at scale.
  • Experience with prompt engineering and fine-tuning open-source LLMs (e.g., Llama, Mistral, Falcon).

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning MLOps LLM Large Language Models Natural Language Processing AWS GCP

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