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Senior AI Engineer - Aether 2026

Aether 2026
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
25 Mei 2026
Deadline
25 Mei 2027

Job Description

Join Aether 2026, a pioneering force in next-generation artificial intelligence. We are dedicated to building the infrastructure that will define the technological landscape of the future. We are looking for a visionary Senior AI Engineer who is passionate about pushing the boundaries of what is possible with deep learning and scalable systems.

In this role, you will not just write code; you will architect the neural pathways of tomorrow. You will work with a world-class team to deploy cutting-edge models that solve complex, real-world problems. If you are driven by innovation and want to leave a lasting impact on the tech industry, we want to meet you.

Responsibilities

  • Design and deploy robust, scalable machine learning pipelines and infrastructure.
  • Conduct research and development to improve model accuracy, latency, and resource efficiency.
  • Collaborate closely with data scientists and product managers to translate business requirements into technical solutions.
  • Implement MLOps best practices, including CI/CD, automated testing, and model monitoring.
  • Lead technical discussions and mentor junior engineers to foster a culture of excellence.
  • Stay at the forefront of AI research to integrate the latest advancements into our production stack.

Qualifications

  • Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
  • 5+ years of professional experience in AI/ML engineering or applied research.
  • Deep proficiency in Python, PyTorch, or TensorFlow.
  • Strong understanding of distributed systems, cloud computing (AWS, GCP, or Azure), and containerization (Docker, Kubernetes).
  • Experience with MLOps tools and version control (Git).
  • Exceptional problem-solving skills and the ability to thrive in a fast-paced, agile environment.

Required Skills

Python Machine Learning Deep Learning PyTorch TensorFlow AWS MLOps Docker Kubernetes Distributed Systems

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