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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Engineer (Generative AI & 2026 Vision)

Nexus AI Labs
San Francisco
Estimated Salary
USD 165.000 – USD 220.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Are you ready to build the artificial intelligence of tomorrow? Nexus AI Labs is seeking a visionary Senior AI Engineer to spearhead our next-generation generative AI platform. In this role, you won't just implement existing models; you will architect the solutions that define the industry landscape for 2026 and beyond.

We are looking for a technical leader who thrives in ambiguity and possesses a deep understanding of Large Language Models (LLMs), prompt engineering, and scalable inference systems. If you are passionate about the future of human-computer interaction, we want to hear from you.

Responsibilities

  • Architect and deploy cutting-edge Generative AI models (LLMs) tailored for enterprise applications.
  • Optimize model inference performance and reduce latency in real-time environments.
  • Implement Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and relevance.
  • Collaborate with cross-functional teams to translate complex business requirements into robust technical solutions.
  • Ensure data privacy, security, and ethical AI practices across all model deployments.
  • Conduct research to identify emerging trends in AI (e.g., Multimodal AI) for future roadmap planning.

Qualifications

  • PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
  • 5+ years of professional experience in software engineering with a focus on Machine Learning/AI.
  • Strong proficiency in Python, PyTorch, or TensorFlow.
  • Deep experience working with LLMs (GPT-4, Claude, Llama 3, etc.) and transformer architectures.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Proven track record of shipping production-grade AI applications.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP LLMs RAG AWS Docker Kubernetes

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