Dandy

Senior Computer Vision, Machine Learning Engineer

Dandy

full-time

Posted on:

Location Type: Hybrid

Location: IndianapolisUnited States

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Salary

💰 $216,750 - $255,000 per year

Job Level

Tech Stack

About the role

  • Build Computer Vision models to extract structure from unstructured, information-dense 3D scans
  • Research SOTA methods for developing models to accomplish 3D generative AI tasks as well as conventional computer vision tasks.
  • Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines
  • Work with massive datasets to develop both generic models as well as fine tune models for specific applications
  • Develop evaluation methods which allow us to establish confidence in our datasets and models
  • Implement best practices for our MLOps pipelines
  • Work closely with product owners on a feature focused team to deliver value quickly to Dandy’s customers

Requirements

  • 8+ years experience post Master's degree, or 5+ years of experience post PhD
  • Extensive experience in Python
  • Extensive experience in SOTA 2D deep learning and/or experience with 3D deep learning
  • Experience with 3D geometric Computer Vision
  • Experience with PyTorch
  • Have immaculate attention to detail and take pride in delivering excellent code and results
  • Masters or PhD in related field
  • Candidates must be able to work onsite in Indianapolis, IN 3 days per week
Benefits
  • healthcare
  • dental
  • mental health support
  • parental planning resources
  • retirement savings options
  • generous paid time off
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
PythonSOTA 2D deep learning3D deep learning3D geometric Computer VisionPyTorchMLOpsmodel evaluationdata processinggenerative AIcomputer vision
Soft Skills
attention to detailpride in delivering resultscollaborationproblem-solvingcommunication
Certifications
Master's degreePhD