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Artificial Intelligence 🏢 Full Time ⭐️ Verified

Generative AI Engineer (2026 Vision)

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

Job Description

The Future of Intelligence Starts Here.

Nexus Future Labs is on a mission to define the Generative AI landscape of 2026. We are seeking a visionary and technically proficient Generative AI Engineer to join our elite engineering team. You will be at the forefront of building autonomous agents, optimizing large language models, and creating synthetic data ecosystems that will power the next generation of enterprise software.

If you are passionate about pushing the boundaries of AI, possess deep technical expertise, and want to shape the future of technology, we want to hear from you.

Responsibilities

  • Architect and deploy scalable generative models using PyTorch and TensorFlow.
  • Design and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and reduce hallucinations.
  • Experiment with new model architectures (e.g., Mixture of Experts, State Space Models) to improve inference speed and token generation quality.
  • Lead the development of autonomous AI agents capable of complex reasoning and multi-step planning.
  • Collaborate with product teams to translate abstract 2026 vision into concrete technical specifications.
  • Ensure ethical AI practices, including bias mitigation and explainability in model outputs.

Qualifications

  • B.S., M.S., or Ph.D. in Computer Science, Mathematics, or a related technical field.
  • 5+ years of experience in Machine Learning, Deep Learning, or Natural Language Processing.
  • Proven expertise in training, fine-tuning, and serving Large Language Models (LLMs).
  • Strong proficiency in Python, C++, and GPU acceleration libraries (CUDA, cuDNN).
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Familiarity with Reinforcement Learning from Human Feedback (RLHF) methodologies.

Required Skills

Python PyTorch TensorFlow LLM GPT RAG Machine Learning Deep Learning CUDA AWS Docker Kubernetes

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