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Senior Generative AI Engineer (2026 Vision)

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Are you ready to build the future? Nexus Future Labs is looking for a Senior Generative AI Engineer to lead our next breakthrough in artificial intelligence. As we approach the technological horizon of 2026, we are seeking a visionary engineer to architect scalable, state-of-the-art Large Language Models (LLMs) that redefine human-machine interaction.

At Nexus Future Labs, we don't just follow trends; we set them. You will work in a collaborative, high-performance environment where your expertise in Deep Learning and Natural Language Processing (NLP) will directly impact millions of users globally. If you are passionate about the intersection of ethics and advanced AI, we want to meet you.

Why Join Us?

  • Work on next-gen AI infrastructure that powers the 2026 roadmap.
  • Competitive compensation and equity packages.
  • Top-tier health, dental, and vision benefits.
  • Flexible remote-first culture with HQ in the heart of San Francisco.

Responsibilities

  • Architect and optimize end-to-end generative AI pipelines for production deployment.
  • Research and implement cutting-edge algorithms in transformer architectures and diffusion models.
  • Collaborate with cross-functional teams to integrate AI capabilities into consumer and enterprise products.
  • Ensure model performance, accuracy, and safety through rigorous testing and bias mitigation.
  • Mentor junior engineers and contribute to the technical vision of the 2026 roadmap.
  • Stay ahead of industry trends to ensure our technology remains future-proof.

Qualifications

  • PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
  • 5+ years of professional experience in Machine Learning or Deep Learning engineering.
  • Strong proficiency in Python, PyTorch, or TensorFlow.
  • Deep understanding of LLM architectures, fine-tuning techniques, and RAG (Retrieval-Augmented Generation).
  • Experience with MLOps, cloud platforms (AWS/GCP), and GPU acceleration.
  • Demonstrable ability to ship high-quality, scalable code in a fast-paced environment.

Required Skills

Python PyTorch TensorFlow Large Language Models Generative AI NLP MLOps Cloud Computing Deep Learning Reinforcement Learning

Ready to Take This Challenge?

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