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Senior AI/ML Engineer - Generative AI & 2026 Roadmap

Nexus Future Systems
San Francisco
Estimated Salary
USD 185.000 – USD 260.000
New
Live Update
5 Juni 2026
Deadline
5 Jun 2027

Job Description

We are seeking a visionary Senior AI/ML Engineer to architect the next generation of intelligent systems for our 2026 roadmap. Nexus Future Systems is at the forefront of Agentic AI and Large Language Model (LLM) integration. In this role, you will not just build models; you will define the future of human-machine interaction. Join a world-class team pushing the boundaries of Generative AI, ensuring scalability, efficiency, and ethical deployment in a rapidly evolving landscape.


Why Join Us?

  • Work with state-of-the-art LLMs (GPT-4, Claude, Llama).
  • Competitive equity package and comprehensive benefits.
  • Flexible remote-first culture with a focus on high-impact work.

Responsibilities

  • Lead the architecture and development of scalable Generative AI pipelines and Agentic workflows.
  • Optimize model inference latency and reduce token costs for enterprise-grade applications.
  • Implement Retrieval-Augmented Generation (RAG) architectures to enhance factual accuracy.
  • Collaborate with product teams to translate 2026 strategic goals into technical roadmaps.
  • Ensure ethical AI practices, including bias detection and data privacy compliance.
  • Mentor junior engineers and conduct code reviews to maintain high engineering standards.

Qualifications

  • Master’s or Ph.D. in Computer Science, Machine Learning, or a related field (or equivalent practical experience).
  • 5+ years of experience in building production-level AI/ML systems.
  • Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Deep experience with LLM fine-tuning, LoRA, and RLHF techniques.
  • Experience with MLOps tools (Docker, Kubernetes, MLflow, Airflow).
  • Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Large Language Models LLM Fine-tuning MLOps RAG Machine Learning Deep Learning AI Architecture Docker Kubernetes

Ready to Take This Challenge?

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