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Information Technology 🏢 Full Time ⭐️ Verified

Senior Artificial Intelligence Engineer (LLMs)

NeuralEdge Dynamics
San Francisco
Salary Estimate
USD 220.000 – USD 280.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

Shape the Future of Generative AI

NeuralEdge Dynamics is at the bleeding edge of enterprise-grade AI solutions. We are seeking a visionary Senior AI Engineer to join our core research and development team in San Francisco. You will play a pivotal role in designing, training, and deploying large-scale language models that transform how global industries operate.

If you are passionate about pushing the boundaries of machine learning and thrive in a high-impact, collaborative environment, we want to hear from you.

Responsibilities

  • Design and implement scalable deep learning architectures and transformer-based models.
  • Optimize large-scale model training pipelines on distributed GPU clusters.
  • Conduct cutting-edge research in RLHF and model alignment strategies.
  • Collaborate with cross-functional product teams to translate complex AI research into high-performance user features.
  • Mentor junior engineers and promote best practices in MLOps and experiment tracking.
  • Evaluate and implement novel inference optimization techniques to reduce latency and costs.
  • Stay at the forefront of AI research by contributing to open-source initiatives and whitepapers.

Qualifications

  • Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of professional experience in deep learning, with at least 2 years focused on LLMs.
  • Deep proficiency in Python and frameworks like PyTorch or JAX.
  • Solid understanding of distributed systems and training orchestration (e.g., Kubernetes, Ray).
  • Hands-on experience with vector databases and RAG (Retrieval-Augmented Generation) architectures.
  • Proven track record of deploying AI models into production environments at scale.
  • Excellent communication skills with the ability to bridge the gap between abstract research and practical engineering.

Required Skills

Artificial Intelligence Python PyTorch Large Language Models MLOps Distributed Systems Transformers

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