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Senior AI Engineer (2026 Vision)

Aether Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Are you ready to define the technological landscape of 2026 and beyond? Aether Dynamics is seeking a visionary Senior AI Engineer to lead the charge in next-generation artificial intelligence. In this pivotal role, you won't just be coding; you will be architecting the systems that will power the global economy in the coming decade.

We are building the future of autonomous systems and generative intelligence. If you have a passion for Large Language Models (LLMs), Reinforcement Learning, and scalable distributed systems, we want to hear from you.

Why join us? We offer top-tier compensation, equity packages, and the opportunity to work on projects that will define the era of AI.

Responsibilities

  • Design and deploy scalable machine learning infrastructure to support rapid business growth.
  • Lead research initiatives in Natural Language Processing (NLP) and Computer Vision to prepare for 2026 trends.
  • Collaborate with cross-functional teams to integrate advanced AI solutions into core product workflows.
  • Optimize model performance and reduce inference latency in high-traffic environments.
  • Establish best practices for MLOps, data governance, and model security.
  • Mentor junior engineers and contribute to the technical vision of the engineering department.

Qualifications

  • Master’s degree in Computer Science, Artificial Intelligence, or a related field.
  • 5+ years of experience building and deploying production-grade machine learning models.
  • Proficiency in Python, PyTorch, or TensorFlow with deep architectural knowledge.
  • Experience with LLMs, Transformers, RAG architectures, and fine-tuning strategies.
  • Strong understanding of distributed systems and cloud platforms (AWS, GCP, or Azure).
  • Excellent communication skills and a proven track record of delivering complex technical projects.

Required Skills

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

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