Role overview
The range for this position is $91,311.00 - $125,553.00 assuming full time status. Starting pay for the successful applicant is dependent on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education.
*A job that shapes a life.
Corning offers you the total package.**
Your well-being is our priority. Our compensation and benefits package supports your health and wellness, financial aspirations, and career from day one.
- Company-wide bonuses and long-term incentives align with key business results and ensure you are rewarded when the company performs well. When Corning wins, we all win.
- As part of our commitment to your financial well-being, we provide a 100% company-paid pension benefit with fixed contributions that grow throughout your career. Combined with matching contributions to your 401(k) savings plan, Corning’s total contributions to your retirement accounts can reach between 7% and 12% of your pay, depending on your age and years of service.
- Our health and well-being benefits include medical, dental, vision, paid parental leave, family building support, fitness, company-paid life insurance, disability, disease management programs, paid time off, and an Employee Assistance Program (EAP) to support you and your family.
- Getting paid for our work is important, but feeling appreciated and recognized for those contributions motivates us much more. That’s why Corning offers a recognition program to celebrate successes and reward colleagues who make exceptional contributions.
We prohibit discrimination on the basis of race, color, gender, age, religion, national origin, sexual orientation, gender identity or expression, disability, veteran status or any other legally protected status.
Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodations to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodation related to disability or religion, please contact us at accommodations@corning.com.
What you'll work on
- Successfully identify the real problem from the customer’s point of view to build and execute predictive maintenance, computer vision, inspection systems, or process modeling work plans that deliver business impact.
- Communicate technical analyses and results to division and manufacturing plant customers.
- Perform exploratory and targeted data analysis using commercial and open-source
data analytics software packages. - Formulate algorithms to develop predictive maintenance or condition-based maintenance strategies for manufacturing equipment. Perform systems design to deploy the developed solutions in production.
- Develop Computer Vision and Deep Learning based solutions to solve problems for various areas of manufacturing such as inspection systems, process workflow, etc.
- Apply multivariate statistical methods and machine learning techniques to find
structure and value in both large and small data sets to identify key process input
variables that can feed process control solutions. - Develop predictive/classification models for use in production.
Write technical reports summarizing development, application, and validation of the technical analysis. - Configure/manage deployment environments for Machine Learning applications including but not limited to on-premise workstations/servers, cloud, or edge devices.
What we're looking for
- Software development experience in C#, C++, or C
- Experience of setting up CUDA environment on Nvidia edge devices
- Familiarity with CI/CD pipelines
- Fluency with Linux and Windows commands-line tools
- Familiarity with OpenCV
- Knowledge of HALCON for Computer Vision is a plus
- Software version control experience (i.e. Git)
- Familiarity with basic concepts of Large Language Models (LLM)
- Familiarity with ETL tools for data extraction, data cleansing, and data manipulation.
- Fluency with SQL
- In-depth knowledge of Deep Learning techniques (e.g., CNN, RNN, YOLO) and proper use of libraries such as PyTorch and TensorFlow
- Familiarity with cloud-based storage and compute environments (AWS, MS Azure)