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JOB SUMMARY:
The research team at ECRS is looking for a talented, experienced individual who is fearless in tackling real world problems with efficient, practical Machine Learning (ML) solutions and demonstrate excellence in computer vision.
RESPONSIBILITIES:
- Research, design, develop and train new machine learning models or adapt and apply existing models and applications.
- Design or develop software systems using design and functional specifications, scientific analysis, good software development practices, and mathematical models.
- Write, update, and maintain computer applications and software packages to handle specific jobs based on machine learning.
- Develop and direct software system testing and validation procedures.
- Review and modify existing software to correct errors, adapt to new hardware, and upgrade interfaces and improve performance.
- Direct software programming and development of corresponding documentation.
REQUIRED QUALIFICATIONS:
- Advanced degree in Computer Science, Statistics, Mathematics or similar, or a comparable career in the industry with an exceptionally good record of successful projects.
- Minimum 3-5 years of industry experience in computer vision delivering successful solutions.
- Good understanding of machine learning, statistics, and mathematics.
- Experience and exceptionally good proficiency in Python and Java, or C/C++.
- Proficient knowledge and experience with image classification, detection, tracking, etc.
- Proficiency in image/video processing and computer vision tools.
- Proficiency in machine learning tools and frameworks such as PyTorch, TensorFlow or similar.
- Experience working with edge devices.
- Experience with modern deep learning techniques in CV including convolutional networks, residual networks, attentional models, etc.
- Familiarity with machine learning workflow.
- Familiarity with cloud-based machine learning platforms.
- Experience in software testing and debugging including the use of automated testing processes.
- Familiarity with relational databases.
- Familiarity with SQL.
- Basic understanding of a retail environment & operations.
- Strong written and verbal communication skills.
PREFERRED QUALIFICATIONS:
- Experience with deep learning infrastructure is a plus.
- Experience with NLP is a plus.
- Proficiency in statistical analysis is a plus.
- Experience with parallel computing technologies or distributed computing techniques is a plus.
ALL APPLICANTS MUST BE AUTHORIZED TO WORK IN THE UNITED STATES.
ABOUT ECRS:
ECRS is a fast-paced, progressive technology company with a wide range of opportunities for quality-oriented, career-minded individuals. Geographically situated in the heart of the Blue Ridge Mountains, ECRS offers the unique opportunity of a high-tech career in a resort college town setting. The ECRS family is made up of energetic, outgoing professionals who love what they do for a living. They are courteous, knowledgeable people who strive for excellence in everything they do. ECRS employees work together in dynamic teams to create, sell, install, and support our best-in-class retail automation solutions.
We believe that acceptance of diversity is a key reason as to why we're successful. All qualified applicants who can demonstrate integrity and competence will receive consideration for employment and advancement without regard to race, color, religion, gender, sexual orientation, disability, age, political affiliation, or national origin.
Skills Required
- Advanced degree in Computer Science, Statistics, Mathematics, or a similar field, or comparable industry experience with an exceptional record of successful projects
- 3–5 years of industry experience delivering successful computer vision solutions
- Strong understanding of machine learning, statistics, and mathematics
- Proficiency in Python and Java, or C/C++
- Experience with image classification, detection, and tracking
- Proficiency in image and video processing and computer vision tools
- Proficiency with machine learning frameworks such as PyTorch or TensorFlow
- Experience working with edge devices
- Experience with modern deep learning techniques, including convolutional networks, residual networks, and attentional models
- Familiarity with machine learning workflows
- Familiarity with cloud-based machine learning platforms
- Experience in software testing and debugging, including automated testing processes
- Familiarity with relational databases
- Familiarity with SQL
- Basic understanding of retail environments and operations
- Strong written and verbal communication skills
- Experience with deep learning infrastructure
- Experience with natural language processing
- Proficiency in statistical analysis
- Experience with parallel or distributed computing technologies
- Authorization to work in the United States
What We Do
Successful retailing is a careful balance of both art and science. ECRS automates the complex science of retail enabling our customers to focus on the art which is what catapults them above competitors and to long-term success. Our comprehensive retail automation solution suite is proven to drive maximum ROI and is backed by award-winning customer training and support. With a 20+ year solid foundation of product success, we take our science seriously with one of the largest, most talented computer science teams in the industry. Our computer science team is balanced with retail analysts and project managers with real-world experience. We also listen to our customers and work with industry partners through extensive trade events, free user conferences, online feedback forms, and simple open communication. Every suggestion a customer brings to our attention is taken seriously and has resulted in some of our most powerful features. From front-store systems including point-of-sale and self-checkout, to comprehensive back office, warehouse, inventory and extensive supply chain automation, ECRS products solve your most challenging loss points with innovative technology designed to truly automate so you can focus on customers and merchandising; the art of running your business.
