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AI & Machine Learning Engineer (2026 Vision)

Nexus Horizon AI
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

About Nexus Horizon AI

We are on a mission to define the technological landscape of 2026 and beyond. We are seeking a visionary AI Engineer to join our elite research and engineering team. You will be at the forefront of developing next-generation Generative AI systems, focusing on Large Language Models (LLMs) and autonomous agents that will transform industries.

Why You Should Apply

Futuristic Impact: Work on projects that will be central to the AI revolution in 2026.

Top-Tier Compensation: Competitive salary, equity, and comprehensive benefits.

Elite Team: Collaborate with Ph.D. researchers and industry veterans.

Responsibilities

  • Architect and deploy scalable machine learning pipelines for production environments.
  • Research and fine-tune state-of-the-art foundation models (e.g., GPT-4, Llama 3) to optimize performance and reduce hallucinations.
  • Implement advanced retrieval-augmented generation (RAG) architectures to enhance data accuracy.
  • Collaborate with product teams to translate complex AI capabilities into intuitive user experiences.
  • Ensure rigorous data privacy, security, and ethical AI compliance standards.
  • Optimize model inference latency and reduce computational costs for real-time applications.

Qualifications

  • PhD or Master's degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
  • 3+ years of professional experience in Deep Learning, NLP, or Generative AI.
  • Strong proficiency in Python, PyTorch, and TensorFlow.
  • Deep understanding of transformer architectures and attention mechanisms.
  • Experience with MLOps, Docker, and Kubernetes for model deployment.
  • Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ACL) or comparable industry experience.

Required Skills

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

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