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Senior AI Engineer (Future-Ready)

Nexus 2026 Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Shape the Future of Intelligence

Join Nexus 2026 Labs, a cutting-edge research firm pioneering the next generation of Artificial General Intelligence. We are looking for a visionary Senior AI Engineer to help architect the systems that will define the technological landscape of the decade. If you are passionate about pushing the boundaries of what is possible with Deep Learning and Neural Networks, this is your opportunity to lead high-impact projects in a dynamic, forward-thinking environment.

We offer a competitive compensation package, full remote flexibility, and the resources to experiment with the most advanced AI models available.

Responsibilities

  • Design, train, and deploy scalable machine learning models and neural networks for production environments.
  • Optimize existing models for speed, accuracy, and resource efficiency using advanced MLOps techniques.
  • Collaborate with cross-functional teams of data scientists, researchers, and product managers to drive innovation.
  • Implement robust monitoring and validation pipelines to ensure model reliability and data integrity.
  • Stay ahead of the curve by integrating the latest research findings into our engineering practices.
  • Conduct code reviews and mentor junior engineers to foster a culture of technical excellence.

Qualifications

  • PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
  • 5+ years of professional experience in Machine Learning Engineering or Data Science.
  • Expert proficiency in Python, PyTorch, TensorFlow, and Scikit-learn.
  • Strong experience with MLOps tools (Docker, Kubernetes, Airflow) and cloud platforms (AWS, GCP).
  • Deep understanding of NLP, Computer Vision, or Reinforcement Learning.
  • Experience with large-scale data processing and distributed computing frameworks.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning MLOps AWS GCP Docker Kubernetes NLP Computer Vision

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