Data Vision Engineer I

MARTINS FAMOUS PASTRY SHOPPE•Chambersburg, PA

11h•Onsite

About The Position

The Data Vision Engineer I will be responsible for developing and optimizing computer vision, deep learning, and data science solutions for multiple internal projects. This individual must have the ability to effectively design, build, and productionize models and software at all stages of development, from research prototype to deployment on edge devices and/or central servers. This employee is expected to have a background spanning computer vision, deep learning, and data science, along with strong software engineering practices, and is passionate about developing production-ready, high-quality software.

Requirements

Bachelor’s Degree in Computer Science, Engineering, Applied Mathematics, or Statistics; 3+ years of related experience; or Master’s Degree or above Computer Science, Engineering, Applied Mathematics, or Statistics
Ability to read and interpret documents such as safety rules, operating and maintenance instructions, and procedure manuals.
Ability to write routine reports and correspondence.
Ability to speak effectively before groups of customers or employees of organization.
Ability to calculate figures and amounts such as discounts, interest, commissions, proportions, percentages, area, circumference, and volume.
Ability to apply concepts of basic algebra, geometry, trigonometry, and calculus.
Knowledge of and experience working with Microsoft Office, Windows, and Linux
Network Fundamentals
Familiarity with Python and C++
Experience in coding machine learning and deep learning systems
Experience with version control (Git) and software engineering best practices
Basic experience with relational and/or non-relational databases (e.g., SQL, MongoDB)
Professional, hands-on experience working on computer vision, deep learning, and/or data science problems in the following subjects: Image Processing and Manipulation, Object Detection and/or tracking, 3D Estimation or Reconstruction, SfM, SLAM, Machine Learning and Deep Learning, Data Science and Statistical Analysis, Predictive and/or Forecasting Models, Large Language Models (LLMs)

Nice To Haves

A strong mathematical and statistical background (e.g., linear algebra, probability, optimization) is a plus.
Experience with Docker/containerization is a plus
Frontend development experience (e.g., React) is a plus
Experience with cameras, and/or mobile robotics; experience designing software systems for edge devices and/or central VM/server environments is a plus

Responsibilities

Perform statistical modeling, data extraction, analysis, construct, evaluate, and tune neural networks
Test and develop your own creative solutions with ample computational resources and ensure required performance and usability is met
Collaborate with various departments and fellow team members to design, develop, and implement novel computer vision, deep learning, and data science solutions to solve relevant manufacturing/logistics problems
Evaluate accuracy and quality of the designed models as well as data sources
Stay up to date with the latest models and changes in the technology
Research and prototype techniques and algorithms across computer vision, deep learning, and data science, including object detection/recognition and predictive or forecasting models
Design and develop production-ready code following established software engineering practices and standards (version control, code review, testing, documentation)
Design system architecture for models and applications deployed to edge devices (e.g., NVIDIA Jetson) and/or central virtual machines/servers
Containerize and deploy applications using Docker, and manage code through Git-based version control workflows
Build, validate, and maintain predictive and/or forecasting models using statistical and machine learning techniques, and support the underlying databases that store and serve their data
Communicate results and implications to colleagues and business partners
Coordinate with application development teams to integrate developed models with existing applications
Train and retrain systems when necessary
Positively impact teams by enhancing applications across our company
Lead projects, report metrics, and improve systems
Develop prototypes fast, and quickly iterate based on feedback