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Senior AI Research Engineer (2026 Vision)

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

Job Description

We are looking for a visionary Senior AI Research Engineer to lead the development of next-generation autonomous systems for the 2026 era. At Nexus Future Labs, we don't just predict the future; we build it.

Join our elite team of data scientists and engineers dedicated to solving humanity's most complex challenges through artificial intelligence. You will be at the forefront of generative modeling, reinforcement learning, and ethical AI architecture.

As a key member of our R&D division, you will define the technical roadmap for our flagship products and mentor the next generation of AI talent.

Responsibilities

  • Lead the research and development of cutting-edge Large Language Models (LLMs) and generative AI frameworks.
  • Optimize deep learning models for high-performance inference and low-latency deployment.
  • Design and implement robust MLOps pipelines to ensure scalable model training and deployment.
  • Collaborate with product managers and engineers to translate research breakthroughs into market-ready features.
  • Conduct rigorous testing and validation of AI models to ensure accuracy, fairness, and safety.
  • Publish peer-reviewed research papers and present findings at top-tier AI conferences.

Qualifications

  • PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
  • 5+ years of professional experience in machine learning, deep learning, or NLP.
  • Expert proficiency in Python, PyTorch, and TensorFlow.
  • Strong experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Proven track record of deploying AI models into production environments.
  • Excellent communication skills with the ability to explain complex technical concepts to diverse stakeholders.

Required Skills

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

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