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Information Technology 🏢 Full Time ⭐️ Verified

Senior Generative AI Architect (2026 Vision)

Quantum Leap Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

We are building the future of intelligent systems for the year 2026 and beyond. Quantum Leap Innovations is seeking a visionary Senior Generative AI Architect to lead our core research and engineering team. You will be responsible for designing, training, and deploying state-of-the-art Large Language Models (LLMs) that power the next generation of enterprise software. If you are passionate about pushing the boundaries of AI, optimizing inference speeds, and creating ethical AI solutions, this is your opportunity to shape the landscape of technology.


Why Join Us?

  • Work on cutting-edge Generative AI projects with a global impact.
  • Competitive compensation package with equity options.
  • Flexible remote-first culture with a hub in San Francisco.
  • Access to the latest hardware for AI research.

Responsibilities

  • Architectural Design: Design and implement scalable, high-performance AI infrastructure and pipelines for LLM fine-tuning and deployment.
  • Model Optimization: Engineer techniques to reduce inference latency and cost while maximizing model accuracy and token generation speed.
  • RAG Implementation: Lead the integration and refinement of Retrieval-Augmented Generation systems to enhance factual accuracy and reduce hallucinations.
  • Team Leadership: Mentor a team of junior engineers and data scientists, conducting code reviews and technical workshops.
  • Research & Development: Stay ahead of the curve in AI research, evaluating new papers and technologies (e.g., MoE, Sparse Attention) to integrate into our stack.

Qualifications

  • Experience: 7+ years of experience in software engineering, with at least 4 years specifically in Machine Learning or Deep Learning.
  • Technical Skills: Proficiency in Python, PyTorch, or TensorFlow. Deep understanding of transformer architectures and attention mechanisms.
  • Education: MS or PhD in Computer Science, Mathematics, or a related technical field is preferred.
  • Tools: Strong experience with cloud platforms (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).
  • Problem Solving: Demonstrated ability to troubleshoot complex mathematical and algorithmic problems in production environments.

Required Skills

Python PyTorch TensorFlow Large Language Models LLM Deep Learning Machine Learning Docker Kubernetes AWS GCP Generative AI RAG NLP

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