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Senior AI/LLM Engineer - 2026 Systems

2026 Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

We are 2026 Systems, a next-generation AI research lab focused on building the foundational intelligence layer for the autonomous economy. We are seeking a visionary Senior AI/LLM Engineer to lead the development of our flagship models. If you are passionate about the future of AGI and want to engineer solutions that transcend current limitations, this is your opportunity to shape the decade ahead.

In this role, you will bridge the gap between theoretical research and production-grade deployment, building systems that are not only intelligent but safe, scalable, and efficient.

Responsibilities

  • Design, train, and fine-tune large language models (LLMs) using PyTorch and TensorFlow.
  • Architect robust Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and reduce hallucinations.
  • Optimize model inference latency and memory footprint for high-volume, low-latency environments.
  • Collaborate with cross-functional teams to integrate AI capabilities into consumer-facing products.
  • Conduct rigorous safety and alignment testing to ensure model outputs adhere to ethical guidelines.
  • Publish research findings and contribute to open-source communities in the AI space.

Qualifications

  • PhD or Master’s degree in Computer Science, Machine Learning, or a related technical field.
  • 5+ years of professional experience in NLP, Deep Learning, or Applied AI.
  • Expert proficiency in Python, C++, and distributed computing frameworks (e.g., Apache Spark, Kubernetes).
  • Deep understanding of transformer architectures, attention mechanisms, and optimization techniques.
  • Experience deploying models on cloud platforms (AWS, GCP, or Azure) with MLOps best practices.
  • Strong problem-solving skills and a track record of delivering complex technical projects on time.

Required Skills

Python PyTorch TensorFlow LLMs NLP MLOps Kubernetes AWS Transformer Models

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