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Information Technology 🏢 Full Time ⭐️ Verified

Senior LLM Architect (The 2026 Vision)

Nexus Future Labs
San Francisco
Estimated Salary
USD 185.000 – USD 260.000
New
Live Update
19 Mei 2026
Deadline
19 Mei 2027

Job Description

The Future is Now. Nexus Future Labs is seeking a visionary Senior LLM Architect to define the autonomous intelligence stack for the year 2026. We are building the next generation of multimodal AI agents that seamlessly integrate into enterprise ecosystems.

As a key architect, you will not just write code; you will shape the architectural paradigms of the next decade. We are looking for someone who thrives in ambiguity and possesses the technical prowess to push the boundaries of Large Language Models (LLMs), reinforcement learning, and cognitive computing.

Why Join Us?

  • Work on cutting-edge generative AI infrastructure.
  • Competitive equity package and 401(k) matching.
  • Flexible remote-first policy with co-working hubs in SF and NYC.

Responsibilities

  • Architect and implement scalable LLM inference pipelines optimized for high-throughput, low-latency environments.
  • Pioneer novel fine-tuning methodologies and RLHF strategies to enhance model reasoning capabilities.
  • Collaborate with cross-functional teams (Data Science, Product, Security) to deploy secure, compliant AI solutions.
  • Research and prototype emerging techniques such as Mixture-of-Experts (MoE) and dynamic token pruning.
  • Mentor junior engineers and foster a culture of technical excellence and innovation.
  • Define technical roadmaps for the "2026 AI Stack" and evaluate competing technologies.

Qualifications

  • PhD or MS in Computer Science, Machine Learning, or a related quantitative field (or equivalent professional experience).
  • Deep expertise in Python, PyTorch, and TensorFlow.
  • Proven track record of publishing at top-tier conferences (NeurIPS, ICML, ACL) or shipping production-grade models at scale.
  • Strong understanding of transformer architectures, attention mechanisms, and optimization techniques.
  • Experience with distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/K8s).
  • Excellent communication skills with the ability to translate complex technical concepts for diverse audiences.

Required Skills

Python PyTorch TensorFlow Large Language Models NLP Machine Learning Deep Learning Distributed Systems Docker Kubernetes AWS Reinforcement Learning Transformers RLHF

Ready to Take This Challenge?

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