CVML Engineer
@ Blue River Technology

Hybrid
$193,000
Hybrid
Full Time
Posted 1 day ago

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XXXXXXXX XXXXXXXXX XXXXXX***** @bluerivertechnology.com
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Job Details

About the Role

Blue River Technology seeks a motivated CVML Engineer to support the See & Spray CVML project. You will collaborate with field operations, data platform teams, labeling services, and product management to implement Data Centric AI practices.

Responsibilities

  • Create and maintain dashboards and visualizations to communicate data-driven insights.
  • Use weak supervision methods for data cleaning and dataset enrichment.
  • Perform model selection, evaluation, and document findings in model release notes.
  • Conduct error analysis and plan data collection for model improvements.
  • Train and fine-tune deep learning models for the See & Spray project.

Required & Preferred Experience

Requirements include a Bachelor's or Master's in Computer Science, Data Science, or related field, and 2+ years in Python or R. Familiarity with PyTorch (or TensorFlow) is preferred, along with skills in dashboard creation and storytelling through data. Prior experience in CVML projects, understanding data modeling, and familiarity with cloud platforms like AWS/Databricks are a plus.

Additional Information

This is a full-time remote role within the United States. Visa sponsorship is not available. The annual base salary range is provided, and compensation is determined by work location and additional factors. Blue River Technology is committed to diversity and inclusion and supports reasonable accommodations.

Key skills/competency

  • CVML
  • Machine Learning
  • Data Visualization
  • Python
  • PyTorch
  • Deep Learning
  • Dashboard Development
  • Data Cleaning
  • Error Analysis
  • Cloud Platforms

How to Get Hired at Blue River Technology

🎯 Tips for Getting Hired

  • Customize your resume: Highlight relevant Python and ML experience.
  • Highlight project work: Emphasize CVML and deep learning projects.
  • Showcase data skills: Include dashboard and visualization expertise.
  • Prepare technical questions: Review model training and evaluation methods.

📝 Interview Preparation Advice

Technical Preparation

Review Python and PyTorch libraries.
Practice building data dashboards.
Study deep learning model fine-tuning.
Refresh weak supervision techniques.

Behavioral Questions

Describe a project collaboration experience.
Explain problem-solving under pressure.
Discuss adapting to feedback quickly.
Share conflict resolution examples.

Frequently Asked Questions