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Artificial Intelligence 🏢 Full Time ⭐️ Verified

Generative AI Research Engineer

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Are you ready to architect the next generation of Artificial Intelligence?

Nexus Horizon Labs is on the hunt for a visionary Generative AI Research Engineer to join our elite R&D division. We aren't just building tools; we are redefining the fabric of digital interaction. If you thrive in high-performance environments and possess a deep understanding of Large Language Models (LLMs), we want to hear from you.

In this pivotal role, you will lead the development of scalable, responsible, and groundbreaking generative models that power our enterprise ecosystem. You will work at the intersection of research and production, ensuring our AI solutions are not only technically superior but also ethically sound.

Responsibilities

  • Lead Model Architecture: Design and implement state-of-the-art Generative AI architectures, including transformers, diffusion models, and large language models (LLMs).
  • Optimization & Scaling: Fine-tune pre-trained models on proprietary datasets and optimize inference performance for latency and throughput.
  • RAG Implementation: Develop and integrate Retrieval-Augmented Generation systems to enhance model accuracy and reduce hallucinations.
  • Research & Innovation: Stay at the forefront of AI research, publishing papers and contributing to open-source communities.
  • Collaboration: Partner with product teams to translate complex research into deployable, user-centric features.

Qualifications

  • Education: MS or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field.
  • Technical Mastery: Proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
  • Experience: 5+ years of experience in machine learning, natural language processing (NLP), or computer vision.
  • Model Fine-tuning: Demonstrated experience in fine-tuning LLMs (e.g., GPT-4, LLaMA) and implementing LoRA/QLoRA techniques.
  • Problem Solving: Ability to tackle complex mathematical and computational challenges with innovative solutions.

Required Skills

Python PyTorch TensorFlow NLP Large Language Models Machine Learning SQL Docker Kubernetes AWS GPT-4 Claude Fine-tuning RAG Ethics in AI

Ready to Take This Challenge?

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