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Senior AI Research Engineer (2026 Vision)

Nexus Horizon Technologies
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

We are seeking a visionary Senior AI Research Engineer to join Nexus Horizon Technologies as we pioneer the innovations of 2026. In this pivotal role, you will lead the charge in developing next-generation artificial intelligence architectures that redefine human-machine interaction. If you are passionate about pushing the boundaries of what is possible in machine learning and possess a drive to shape the future of technology, we want to hear from you.

At Nexus Horizon, we are committed to excellence and innovation. You will have the opportunity to work with state-of-the-art hardware and collaborate with world-class experts in a dynamic, fast-paced environment.

Responsibilities

  • Lead the research and development of advanced neural network architectures for next-generation AI models.
  • Optimize model inference and training pipelines for high-scale distributed systems to ensure real-time performance.
  • Collaborate with cross-functional product and engineering teams to integrate AI solutions into scalable product ecosystems.
  • Conduct rigorous experimentation, statistical analysis, and validation to improve model accuracy, robustness, and fairness.
  • Publish cutting-edge research papers and actively contribute to the open-source machine learning community.
  • Define technical strategies for long-term research initiatives and mentor junior engineers and researchers.

Qualifications

  • Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
  • 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing (NLP).
  • Expert proficiency in Python, PyTorch, TensorFlow, and scikit-learn.
  • Strong understanding of statistical modeling, optimization algorithms, and distributed computing.
  • Experience with cloud platforms (AWS, GCP) and MLOps tools such as Kubeflow or MLflow.
  • Demonstrated ability to translate complex research concepts into practical, production-ready applications.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Distributed Systems MLOps AWS GCP

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