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Senior AI Engineer - Future Systems (2026 Tech)

Aether Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Are you ready to define the technology of tomorrow? At Aether Labs, we are pioneering the 2026 era of artificial intelligence. We are seeking a visionary Senior AI Engineer to architect the next generation of autonomous decision-making systems. If you are passionate about pushing the boundaries of what is possible in machine learning and want to work on projects that will shape the future of industry, we want to hear from you.

Our team focuses on building scalable, secure, and efficient AI infrastructure that operates at the edge and in the cloud. You will collaborate with world-class researchers and engineers to solve complex problems in natural language processing, computer vision, and reinforcement learning.

Responsibilities

  • Design, develop, and deploy cutting-edge machine learning models using Python, TensorFlow, and PyTorch.
  • Optimize inference pipelines and reduce latency for real-time AI applications.
  • Collaborate with cross-functional teams to integrate AI solutions into production environments.
  • Conduct research and experiments to improve model accuracy and robustness.
  • Lead architectural discussions regarding scalability, security, and performance.
  • Mentor junior engineers and provide technical guidance on best practices.

Qualifications

  • Master’s degree or Ph.D. in Computer Science, Mathematics, or a related technical field.
  • 5+ years of professional experience in software engineering, with a focus on AI/ML.
  • Strong proficiency in Python, C++, and modern deep learning frameworks.
  • Experience with distributed systems, cloud platforms (AWS, GCP, or Azure), and containerization (Docker, Kubernetes).
  • Proven track record of deploying models to production environments.
  • Excellent communication skills and the ability to articulate complex technical concepts.

Required Skills

Python Machine Learning Deep Learning TensorFlow PyTorch AWS Kubernetes Distributed Systems Natural Language Processing

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