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Senior AI Engineer (2026 Vision)

Nexus Future Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

We are seeking a visionary Senior AI Engineer to join our elite team at Nexus Future Technologies. As we prepare for the next generation of intelligent systems, you will play a pivotal role in architecting scalable, ethical, and high-performance machine learning solutions. This is a unique opportunity to define the technical roadmap for 2026 and beyond, working with state-of-the-art models and distributed computing systems.

Why Join Us?

  • Work on cutting-edge AI infrastructure that will shape the future of the industry.
  • Competitive compensation package with equity options.
  • Flexible remote-first culture with premium office amenities in the heart of SF.

Responsibilities

  • Design, develop, and deploy advanced machine learning models for production environments.
  • Optimize inference latency and model accuracy to support real-time applications.
  • Collaborate with cross-functional teams to integrate AI capabilities into core products.
  • Establish MLOps pipelines to ensure reproducibility and automated deployment.
  • Conduct research on emerging AI paradigms (e.g., Transformers, LLMs) to stay ahead of the curve.
  • Ensure all AI systems adhere to strict ethical guidelines and data privacy standards.

Qualifications

  • Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of professional experience in software engineering and machine learning.
  • Proficiency in Python, PyTorch, or TensorFlow.
  • Strong understanding of distributed systems, cloud architecture (AWS/GCP), and containerization (Docker/Kubernetes).
  • Experience with LLM fine-tuning and RAG architectures.
  • Excellent problem-solving skills and ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow MLOps AWS Kubernetes Machine Learning Deep Learning Distributed Systems

Ready to Take This Challenge?

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