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Artificial Intelligence 🏢 Full Time ⭐️ Verified

Future-Ready AI & Machine Learning Engineer

Nexus Horizon Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Are you ready to define the future of technology in 2026? Nexus Horizon Technologies is seeking a visionary Future-Ready AI & Machine Learning Engineer to architect the next generation of intelligent systems.

In this pivotal role, you won't just use existing tools; you will shape the paradigms of Agentic AI, Autonomous Agents, and Generative Multimodal Models that will dominate the enterprise landscape of the coming years. We are looking for a builder who is obsessed with scalability, ethical AI, and creating systems that think beyond code.

Join a team where innovation isn't just a buzzword—it's the only metric that matters. You will work directly with C-level executives to deploy solutions that are 3-5 years ahead of the market curve.

Responsibilities

  • Design and deploy scalable Agentic AI workflows capable of autonomous decision-making and complex reasoning.
  • Optimize large language models (LLMs) for specific enterprise use cases, focusing on inference speed and accuracy.
  • Build and maintain robust MLOps pipelines ensuring seamless deployment from prototype to production.
  • Research and implement cutting-edge techniques in Multimodal AI (text, image, and audio synthesis).
  • Ensure data privacy and ethical AI standards are integrated into every layer of the architecture.

Qualifications

  • 5+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
  • Expert proficiency in Python, PyTorch, or TensorFlow.
  • Strong understanding of Vector Databases and RAG (Retrieval-Augmented Generation) architectures.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Proven track record of shipping production-level AI applications.

Required Skills

Python PyTorch Machine Learning Deep Learning MLOps AWS Kubernetes Agentic AI RAG Vector Databases

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