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Information Technology 🏒 Full Time ⭐️ Verified

Senior LLM Engineer

Nebula AI Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
24 Mei 2026
Deadline
24 Mei 2027

Job Description

Join the Future of Intelligence.

We are building the generative AI infrastructure for the next decade. At Nebula AI Labs, we don't just predict the future; we engineer it. We are seeking a visionary Senior LLM Engineer to lead our research and development efforts in creating scalable, safe, and high-performance Large Language Models. If you are passionate about pushing the boundaries of NLP and want to define the standards for AI in 2026, we want to hear from you.


Why Join Us?
We offer a competitive salary, equity packages, and a remote-first culture that values innovation over bureaucracy. You will work with state-of-the-art hardware and collaborate with the brightest minds in the industry.

Responsibilities

  • Architect and implement scalable inference pipelines for large language models (LLMs) including GPT-4, Llama 3, and Claude.
  • Lead the research and development of novel fine-tuning and RAG (Retrieval-Augmented Generation) techniques to enhance model accuracy and reduce hallucinations.
  • Optimize model serving performance for low-latency, high-throughput production environments using MLOps best practices.
  • Collaborate with data scientists and product managers to translate business requirements into cutting-edge technical solutions.
  • Ensure ethical AI practices, including bias mitigation and safety alignment protocols.
  • Contribute to open-source communities and publish research papers on large-scale language model improvements.

Qualifications

  • PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field (or equivalent professional experience).
  • 5+ years of professional experience in machine learning, deep learning, or natural language processing.
  • Strong proficiency in Python, PyTorch, or TensorFlow.
  • Deep understanding of transformer architectures, attention mechanisms, and model training methodologies.
  • Experience deploying models via Kubernetes, Docker, and cloud platforms (AWS/GCP/Azure).
  • Proven track record of improving model performance metrics (BLEU, ROUGE, perplexity) in production settings.
  • Excellent communication skills and ability to mentor junior engineers.

Required Skills

Python PyTorch TensorFlow LLM Large Language Models Machine Learning Deep Learning NLP MLOps Kubernetes Docker AWS GPT-4 Fine-tuning RAG

Ready to Take This Challenge?

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