Deep Learning /Computer Vision Lead Engineer - Stealth Computer Vision Industrial Safety Venture
As a DL/CV Lead you will
- Help build and lead a team of experienced research scientists and engineers to research, design, implement and evaluate Dl/CV models for safety applications.
- Help architect and end to end DL/CV system that operates at global scale. 2+ years of prior experience developing DL/CV systems at scale highly preferred
- Work closely with back/front end and engineering teams to drive scalable, production-ready implementations
- Collaborate with teams across the company and serve as an internal expert on technical issues
- Document technical work as part of the product development process.
- Support patent application publishing process
- Contribute to our evolving cloud infrastructure, data engineering pipeline, and analysis stack
- Contribute to our data strategy design and implementation
- Identify technical challenges, define requirements and prioritize efforts
- Assist with defining requirements and architectures for next-generation computer vision/ machine learning products
- Contribute to scientific software engineering efforts, utilizing professional coding standards and participating in reviewing PRs
- Contribute data enrichment and data monetization process
Desired Expertise & Experience
- PhD in Computer Science, Engineering, Computational Physics OR Master's degree (related degree above) and +2 years relevant work experience.
- Previous experience in DL/CV products is required.
- Experience with sensor-fusion highly desirable
- An understanding of SLAM/Location technologies helpful
- An understanding of cloud based vs. edge compute based AI-architectures helpful
- Machine Learning: classification, regression, clustering; Demonstrated ability to apply deep learning and convolutional neural network approaches for machine learning problems.
- Algorithms: Fundamental data types (stacks, queues, etc.); Sorting algorithms (quicksort, mergesort, etc.); Dynamic programming
- Strong communication skills to work with stakeholders, team members and other engineering team colleagues
- Proficiency with programming languages such as: Python and capability in writing production level code. Experience in using Tensorflow or Pytorch or Caffe or Keras are needed.
- Familiarity with collaborative software engineering practices, including version control (Git), code reviews, JIRA, Confluence.
- Familiarity with cloud computing and developing cloud based APIs
- Ability to architect and implement computer vision solutions with specific skills mentioned in rows above; Strong foundation in machine learning, mathematics, statistics, with demonstrated professional or academic experience
- Must be willing and able to travel up to ~10% of time