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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Engineer

Nexus Horizon
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

We are seeking a visionary Senior AI Engineer to join our elite team in San Francisco. As we prepare for the technological leaps of 2026, you will be at the forefront of developing scalable, next-generation artificial intelligence solutions.

At Nexus Horizon, we don't just build software; we architect the future. You will work on projects that redefine human-machine interaction, leveraging state-of-the-art Large Language Models (LLMs) and predictive analytics to solve complex global challenges.

Responsibilities

  • Architect Next-Gen AI Systems: Design and deploy robust machine learning pipelines capable of handling 2026-scale data volumes and complexity.
  • Lead Research & Development: Spearhead research initiatives in Natural Language Processing (NLP), Computer Vision, and Generative AI.
  • Model Optimization: Continuously optimize model inference speeds and accuracy to ensure real-time, low-latency user experiences.
  • Cross-Functional Leadership: Collaborate with product managers, engineers, and designers to integrate advanced AI models into core products seamlessly.
  • Talent Development: Mentor junior engineers, conduct code reviews, and establish best practices for AI governance and ethics.
  • Scalability Engineering: Implement containerized solutions using Kubernetes and Docker to ensure system resilience and scalability.

Qualifications

  • Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
  • Experience: 5+ years of professional experience building and deploying production-grade AI applications and machine learning models.
  • Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and CUDA. Strong understanding of deep learning architectures (RNNs, Transformers, GANs).
  • LLM Expertise: Deep knowledge of Large Language Models, prompt engineering, fine-tuning strategies, and RAG (Retrieval-Augmented Generation) pipelines.
  • Cloud Infrastructure: Extensive experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (MLflow, SageMaker, Vertex AI).
  • Problem Solving: Exceptional ability to translate abstract research concepts into practical, high-impact engineering solutions.

Required Skills

Python TensorFlow PyTorch Machine Learning Deep Learning NLP LLM AWS GCP Kubernetes Docker MLOps SQL Data Structures Algorithms

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