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Principal AI Engineer - Nexus 2026

Nexus 2026 Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Are you ready to define the technological landscape of the future? Nexus 2026 Labs is seeking a visionary Principal AI Engineer to spearhead our core research division. We are building the infrastructure for tomorrow, and we need a technical expert to lead our initiatives in Generative AI and Predictive Modeling.


In this role, you will bridge the gap between theoretical AI research and scalable enterprise solutions. You will be instrumental in the Nexus 2026 roadmap, ensuring our platforms remain at the forefront of innovation.

Responsibilities

  • Lead the architectural design of next-generation neural networks and machine learning pipelines.
  • Oversee the end-to-end development lifecycle of AI products, from prototype to production deployment.
  • Mentor and coach junior engineers and data scientists, fostering a culture of technical excellence.
  • Collaborate with C-level stakeholders to translate business objectives into technical strategies.
  • Optimize existing models for latency, throughput, and cost-efficiency in high-traffic environments.
  • Stay ahead of industry trends, particularly in Large Language Models (LLMs) and autonomous agents.

Qualifications

  • PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
  • Minimum of 8 years of experience in software engineering and machine learning, with at least 3 years in a leadership capacity.
  • Expert proficiency in Python, C++, and deep learning frameworks (PyTorch, TensorFlow, JAX).
  • Strong background in distributed systems, cloud computing (AWS/Azure/GCP), and MLOps.
  • Proven experience deploying AI systems that handle millions of requests per day.
  • Exceptional problem-solving skills and a passion for ethical AI development.

Required Skills

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

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