Remote AI Innovation Engineer — Scalable ML Production

Bright Vision Technologies

United States

Remote

USD 135,000 - 210,000

Full time

9 days ago

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Job summary

Bright Vision Technologies seeks an AI Innovation Engineer to bridge cutting-edge applied research and production engineering, designing and shipping advanced ML systems. The role blends scientific rigor with practical software engineering, requiring deep understanding of modern ML and the ability to build robust, scalable production pipelines with strong observability.

The ideal candidate stays current with AI research, critically evaluating new techniques for real-world applicability and

Qualifications

  • Master's or PhD in Computer Science, Machine Learning, Statistics, or a closely related field; or equivalent applied experience.
  • Six or more years of combined research and applied ML engineering experience.
  • Strong proficiency in Python and modern ML frameworks such as PyTorch or JAX.
  • Hands-on experience training, fine-tuning, and evaluating deep learning models at non-trivial scale.
  • Solid grounding in mathematics, statistics, and the theoretical foundations of modern ML.
  • Experience taking ML models from research prototype to production with appropriate observability and safeguards.
  • Familiarity with distributed training, mixed-precision training, and accelerator hardware.
  • Strong written and verbal communication skills, including ability to explain complex methods clearly.
  • Demonstrated ability to read, evaluate, and adapt techniques from current research literature.
  • Track record of shipping impactful applied AI projects.

Skills

Python
PyTorch
JAX
Production ML
Distributed training
Communication
Math & stats

Education

Master's/PhD in CS/ML/Statistics

Job description

Bright Vision Technologies seeks an AI Innovation Engineer to bridge cutting-edge applied research and production engineering, designing and shipping advanced ML systems. The role blends scientific rigor with practical software engineering, requiring deep understanding of modern ML and the ability to build robust, scalable production pipelines with strong observability.

The ideal candidate stays current with AI research, critically evaluating new techniques for real-world applicability and

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