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Information Technology 🏢 Full Time ⭐️ Verified

Senior Generative AI Engineer (2026 Vision)

Nexus Core Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Are you ready to architect the intelligent systems of tomorrow?

Nexus Core Systems is pioneering the future of Generative AI and Autonomous Agents. We are seeking a visionary Senior AI Engineer to join our elite team and define the roadmap for 2026 and beyond. In this role, you will not just write code; you will build the cognitive frameworks that power the next generation of digital experiences.

Join us in shaping the intersection of human creativity and artificial intelligence. If you are passionate about Large Language Models (LLMs), Multimodal AI, and building systems that understand the world, we want to hear from you.

Responsibilities

  • Architect & Develop: Lead the design and implementation of cutting-edge Generative AI models and LLMs tailored for enterprise scalability.
  • Roadmap Strategy: Define the technical roadmap for AI innovation, ensuring alignment with the company's 2026 vision and market demands.
  • Multimodal Systems: Build and optimize multimodal AI systems that integrate text, image, and audio data seamlessly.
  • MLOps Excellence: Establish robust CI/CD pipelines for machine learning, ensuring model deployment, monitoring, and retraining are automated and efficient.
  • Research & Experimentation: Stay ahead of the curve by researching the latest breakthroughs in AI safety, alignment, and performance optimization.
  • Collaboration: Partner with product managers, designers, and engineers to translate complex AI capabilities into intuitive user experiences.

Qualifications

  • Experience: 5+ years of professional experience in software engineering or machine learning, with a focus on AI/ML.
  • Technical Stack: Deep proficiency in Python, PyTorch, or TensorFlow; strong experience with Hugging Face Transformers and LangChain.
  • Model Optimization: Demonstrated expertise in fine-tuning, RAG (Retrieval-Augmented Generation), and model quantization.
  • Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
  • Problem Solving: Exceptional ability to troubleshoot complex algorithmic issues and optimize for latency and throughput.
  • Communication: Excellent verbal and written communication skills; ability to explain complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning LLMs NLP MLOps Cloud Computing (AWS/GCP/Azure)

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