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Senior AI Research Engineer (2026 Vision)

Nexus Horizon AI
San Francisco
Estimated Salary
USD 185.000 – USD 260.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

We are redefining the boundaries of artificial intelligence. As we approach the transformative year of 2026, Nexus Horizon AI is seeking a pioneering Senior AI Research Engineer to spearhead our next-generation generative models and agentic workflow systems.

In this role, you won't just be maintaining the status quo; you will architect the foundational systems that will power autonomous agents, advanced Natural Language Processing (NLP), and adaptive machine learning algorithms for the decade ahead. If you are passionate about pushing the limits of what's possible in AI and thrive in a fast-paced, high-impact environment, we want to hear from you.

Why Join Us?

  • Future-Forward Tech Stack: Work with the latest in LLMs, Transformers, and reinforcement learning.
  • High Impact: Your work will directly influence the roadmap for autonomous AI agents.
  • Competitive Compensation: Base salary + equity + performance bonuses.

Responsibilities

  • Design and implement scalable machine learning models for next-generation Generative AI applications.
  • Research novel architectures for reasoning, planning, and autonomous agent behavior (2026 roadmap).
  • Optimize deep learning inference pipelines to reduce latency and increase throughput.
  • Collaborate with cross-functional teams of engineers, product managers, and data scientists to translate research into production-ready features.
  • Stay at the forefront of the AI landscape, monitoring emerging trends in Quantum Computing and Neuro-symbolic AI.

Qualifications

  • Master’s or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field.
  • 5+ years of professional experience in machine learning, deep learning, or AI research.
  • Expert proficiency in Python, PyTorch, or TensorFlow.
  • Deep understanding of Large Language Models (LLMs), fine-tuning, and RAG architectures.
  • Strong problem-solving skills and the ability to work independently in a research-driven environment.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP LLMs Generative AI CUDA Reinforcement Learning

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