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Senior AI Engineer (Vision 2026) - San Francisco, CA

Nexus Horizon AI
San Francisco
Estimated Salary
USD 190.000 – USD 260.000
Live Update
10 Juli 2026
Deadline
10 Jul 2027

Job Description

We are Nexus Horizon AI, a pioneer in next-generation generative intelligence. We are looking for a visionary Senior AI Engineer to join our core engineering team and help architect the solutions of the future. As we build towards our 2026 roadmap, we need a technical leader who thrives on ambiguity and is passionate about pushing the boundaries of Large Language Models (LLMs) and autonomous agents.

In this role, you will not just write code; you will define the technical DNA of our products. You will work alongside world-class researchers and engineers to build scalable, efficient, and safe AI systems.

Why Nexus Horizon?

  • Impact: Your work will directly influence the trajectory of AI adoption in enterprise.
  • Future-Proof: We are hiring for the long term, specifically targeting the technological advancements required for 2026.
  • Equity: Competitive equity package for early-stage impact.

Responsibilities

  • Design and implement scalable machine learning infrastructure capable of handling petabyte-scale data processing.
  • Lead the development and fine-tuning of proprietary LLMs to enhance model performance and reduce inference latency.
  • Collaborate with product and research teams to translate business requirements into technical AI architectures.
  • Implement robust MLOps pipelines to ensure continuous integration and deployment of AI models.
  • Mentor junior engineers and conduct code reviews to maintain high technical standards across the team.
  • Research emerging AI trends and evaluate their applicability to Nexus Horizon’s product roadmap.

Qualifications

  • Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
  • Minimum of 5 years of professional experience in AI/ML engineering, with at least 2 years focusing on NLP or Generative AI.
  • Expert proficiency in Python, PyTorch, or TensorFlow.
  • Deep understanding of transformer architectures, distributed training, and model optimization techniques.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Strong grasp of software engineering best practices, including version control (Git) and agile methodologies.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP LLMs MLOps AWS Kubernetes Docker Generative AI

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