Remote ML Research Engineer: Lab-to-Production Impact

Bright Vision Technologies; Plymouth (MN); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a Machine Learning Research Engineer to bridge cutting‑edge applied research and production engineering. You will design and ship advanced ML systems across NLP, vision, recommendations, and structured data, emphasizing rigorous evaluation and scalable pipelines.

The role requires 6+ years of experience, strong Python and ML framework skills (PyTorch or JAX), and a track record of taking models from research to production with observability.

Qualifications

• Master’s or PhD in Computer Science, ML, Statistics, or related field or equivalent applied experience.
• Six+ years combined research and applied ML engineering experience.
• Strong proficiency in Python and ML frameworks such as PyTorch or JAX.
• Hands-on experience training and evaluating deep learning models at scale.
• Experience taking ML models from research to production with observability.

Responsibilities

• Design, prototype, and evaluate applied AI solutions across NLP, vision, recommendation, and structured data.
• Translate business problems into ML formulations with clear success metrics.
• Build production‑quality training and inference pipelines.
• Collaborate with ML platform engineers to optimize compute and resources.
• Develop tooling for dataset construction, labeling, validation, and monitoring.

Skills

Python

Machine Learning

PyTorch

JAX

Distributed training

Observability

Communication

Education

Master’s or PhD in CS/ML/Statistics

6+ years experience in ML research/engineering

Tools

PyTorch

JAX

Job description

Bright Vision Technologies is seeking a Machine Learning Research Engineer to bridge cutting‑edge applied research and production engineering. You will design and ship advanced ML systems across NLP, vision, recommendations, and structured data, emphasizing rigorous evaluation and scalable pipelines.

The role requires 6+ years of experience, strong Python and ML framework skills (PyTorch or JAX), and a track record of taking models from research to production with observability.