Remote AI Research Engineer: From Research to Production

Bright Vision Technologies; Nashua (NH); On-site; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Research Engineer to bridge cutting-edge applied research and production ML engineering for a fully remote role in the U.S. The candidate will design, implement, and productionize advanced ML systems across multiple domains, with emphasis on rigorous experimentation and scalable pipelines.

The role requires deep knowledge of modern ML techniques, collaboration with product and domain experts, and a track record of shipping impactful AI projects.

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.
• Familiarity with distributed training, mixed-precision training, and accelerator hardware.

Responsibilities

• Design, prototype, and evaluate applied AI solutions across NLP, vision, recommendation, and structured data.
• Translate ambiguous business problems into well-scoped ML formulations with clear metrics.
• Stay current with DL, LLMs, and assess applicability to internal use cases.
• Build production-quality training and inference pipelines using modern ML frameworks.
• Collaborate with ML platform engineers to optimize compute, storage, and accelerators.
• Develop model safety, reliability, and evaluation processes for deployment.

Skills

Python

Communication

Education

Master’s or PhD in CS/ML/Statistics or related

Tools

PyTorch

JAX

Job description

Bright Vision Technologies is seeking an AI Research Engineer to bridge cutting-edge applied research and production ML engineering for a fully remote role in the U.S. The candidate will design, implement, and productionize advanced ML systems across multiple domains, with emphasis on rigorous experimentation and scalable pipelines.

The role requires deep knowledge of modern ML techniques, collaboration with product and domain experts, and a track record of shipping impactful AI projects.