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Senior AI Engineer - 2026 Predictive Tech

Chronos Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Shape the Future with Our 2026 Predictive AI Stack

Chronos Future Systems is at the forefront of next-generation predictive technology. We are looking for a visionary Senior AI Engineer to lead the architecture and development of our proprietary 2026 neural processing engine. If you are passionate about pushing the boundaries of what is possible in artificial intelligence and want to build the infrastructure of tomorrow, we want to hear from you.

As a key member of our engineering team, you will be responsible for designing scalable, fault-tolerant systems that leverage the 2026 predictive framework. You will work closely with data scientists, researchers, and product leads to translate complex algorithms into production-ready software that impacts millions of users globally.

Responsibilities

  • Design and implement the core architecture for the 2026 predictive AI framework, ensuring high performance and low latency.
  • Optimize deep learning models for real-time inference on distributed cloud infrastructure.
  • Lead code reviews and establish best practices for AI engineering within the team.
  • Collaborate with cross-functional teams to define product requirements and technical specifications.
  • Mentor junior engineers and foster a culture of continuous learning and innovation.
  • Monitor system health and performance, implementing robust CI/CD pipelines for model deployment.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field; Ph.D. preferred.
  • 5+ years of professional experience in Machine Learning, Deep Learning, or Artificial Intelligence.
  • Proficiency in Python, C++, and GPU programming (CUDA).
  • Strong understanding of neural network architectures and optimization techniques.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Proven track record of deploying large-scale ML models in production environments.

Required Skills

Artificial Intelligence Machine Learning Python Deep Learning Neural Networks Cloud Computing AWS GCP Docker Kubernetes PyTorch TensorFlow

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