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Senior AI/ML Engineer - Nexus 2026

Nexus 2026
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Join Nexus 2026, a premier think-tank and engineering firm, in our mission to architect the technological landscape of the future. We are seeking a visionary Senior AI/ML Engineer to lead our advanced research division. In this pivotal role, you will design and deploy scalable neural networks and machine learning models that solve complex, real-world problems targeting the 2026 market era.

We value innovation, autonomy, and technical excellence. You will have the opportunity to work with state-of-the-art tools, collaborate with top-tier researchers, and directly influence the strategic direction of our flagship products.

Key Highlights:

  • Work on cutting-edge AI initiatives that define the next decade of technology.
  • Competitive compensation package with equity opportunities.
  • Flexible hybrid work model in the heart of San Francisco.

Responsibilities

  • Design, develop, and deploy scalable machine learning models and deep learning architectures.
  • Lead the research and implementation of novel algorithms to improve predictive accuracy and system performance.
  • Optimize data pipelines for high-volume processing and real-time inference.
  • Mentor and guide a team of junior data scientists and engineers.
  • Collaborate with cross-functional product teams to translate business requirements into technical AI solutions.
  • Ensure adherence to ethical AI guidelines and data governance standards.

Qualifications

  • Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of professional experience in AI/ML engineering, preferably in a startup or high-growth environment.
  • Expert proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
  • Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies.
  • Familiarity with MLOps tools (MLflow, Kubeflow) and version control (Git).
  • Proven track record of delivering production-ready AI solutions.

Required Skills

Python Machine Learning Deep Learning PyTorch TensorFlow AWS GCP MLOps Data Engineering

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