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Information Technology 🏢 Full Time ⭐️ Verified

Senior Generative AI Engineer (2026 Vision)

Nexus Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Are you ready to architect the AI of tomorrow?

Nexus Future Systems is looking for a visionary Senior Generative AI Engineer to lead the next evolution of our intelligent platform. As we look toward 2026, we are building the infrastructure for Agentic AI and autonomous decision-making systems.

In this role, you won't just write code; you will define the ethical frameworks and technical standards for the future of human-computer interaction. If you are passionate about Large Language Models (LLMs), fine-tuning, and building scalable AI infrastructure, we want to meet you.

Why Join Us?
We offer top-tier compensation, remote-first flexibility, and the chance to work on projects that will shape the next decade of technology.

Responsibilities

  • Architect Next-Gen LLMs: Design, train, and fine-tune large-scale generative models using Transformer architectures to solve complex business problems.
  • Optimize Inference Pipelines: Build high-performance, low-latency systems for deploying AI models in production environments with a focus on cost-efficiency.
  • Agentic AI Development: Develop autonomous agents capable of multi-step reasoning, tool usage, and real-time environment interaction.
  • Ethical AI Oversight: Implement robust guardrails and safety protocols to ensure AI outputs are fair, unbiased, and compliant with emerging regulations.
  • Collaborate with Research: Partner with data scientists and researchers to bridge the gap between theoretical models and practical engineering applications.

Qualifications

  • Master’s or PhD in Computer Science, Machine Learning, or a related field. (Bachelor’s with 5+ years of experience considered).
  • Expertise in Python and Deep Learning frameworks such as PyTorch or TensorFlow.
  • Proven experience working with Large Language Models (GPT, Claude, Llama, etc.) and RAG (Retrieval-Augmented Generation) architectures.
  • Experience with MLOps tools (Docker, Kubernetes, MLflow, or Ray).
  • Strong mathematical foundation in Linear Algebra, Calculus, and Probability Statistics.
  • Excellent communication skills to translate complex technical concepts for diverse stakeholders.

Required Skills

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

Ready to Take This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

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