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Senior AI Research Engineer - Generative Models

Nexus Horizon AI
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

We are building the cognitive infrastructure for the year 2026. Nexus Horizon AI is seeking a visionary Senior AI Research Engineer to spearhead the development of next-generation Large Language Models and autonomous agent systems. You will be at the forefront of merging neuroscience with artificial intelligence, creating systems that don't just process data but understand intent.

Why join us?

  • Work on the bleeding edge of AGI (Artificial General Intelligence) research.
  • Competitive equity package and top-tier healthcare.
  • Flexible remote-first culture with quarterly innovation sprints.

Ready to define the future of intelligence? Apply today.

Responsibilities

  • Architect and deploy scalable generative AI models capable of zero-shot learning and complex reasoning.
  • Optimize inference pipelines for low-latency, high-throughput environments using distributed computing frameworks.
  • Conduct cutting-edge research in transformer architectures and reinforcement learning for autonomous decision-making.
  • Mentor junior data scientists and research engineers to foster a culture of innovation and technical excellence.
  • Collaborate with product teams to translate theoretical AI breakthroughs into tangible user-facing features.
  • Evaluate model performance rigorously, focusing on fairness, transparency, and ethical AI deployment.

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on AI/ML.
  • 5+ years of professional experience building production-level machine learning systems.
  • Deep expertise in PyTorch, TensorFlow, or JAX.
  • Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR) or open-sourcing significant AI libraries.
  • Strong understanding of NLP, Computer Vision, or Reinforcement Learning fundamentals.
  • Experience with MLOps tools (Kubeflow, MLflow) and cloud platforms (AWS, GCP, Azure).

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP MLOps Distributed Systems Reinforcement Learning Cloud Computing San Francisco California Full Time

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