Job Description Summary

BD Parata Software Vision Engineering team has a Software Vision Engineer Internship for 3 months June through August. The high-level work plan envisioned for this opportunity would include the following milestones.

At the beginning is developing a proof of concept of incorporating a data pipeline to manage different datasets, management of datasets, and incorporation of a data pipeline through the development of the proof of concept called VisionWatch. This is an internal tool and application to assist the Vision team under Blister to manage, develop, and track the various datasets for training and validating

Second component is developing and handing the datasets to the Automation aspect to ensure that the training team can begin training the Deep Learning models based on the images and annotations that have been provided

Job Description

We are the makers of possible 

 

BD is one of the largest global medical technology companies in the world. Advancing the world of health™ is our Purpose, and it’s no small feat. It takes the imagination and passion of all of us—from design and engineering to the manufacturing and marketing of our billions of MedTech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities. 

 

We believe that the human element, across our global teams, is what allows us to continually evolve. Join us and discover an environment in which you’ll be supported to learn, grow and become your best self. Become a maker of possible with us. 

BD Parata Computer Vision Portfolio currently serves 4 use cases in our Adherence Packaging SW Portfolio with Blister, Perl, MedInspect and Dimensio algorithms that are leveraging computer vision and AI/ML to improve Pharmacy workflow and Pharmacist Verification 2 to ensure accuracy of the prescription fulfillment process.  The use of Computer Vision Technologies serves to provide guidance to the end users to identify what needs to be corrected/reviewed and reduce Pharmacist Fatigue.  The Computer Vision strategy is to continuously improve computer vision and algorithms across our globally installed assets by increasing automation, identifying and defining features and review extensibility to more product areas that could benefit from computer vision in their workflows to improve accuracy and performance of each product.​ 

Pharmacy Automation is the fastest growing portfolio within the MMS business unit because pharmacies are investing like never before to address emerging challenges and opportunities arising from fundamental changes to their traditional business models. 

• ​Changing Economic Model: Reimbursement trends, labor shortages and rising labor costs compress margins for labor-intensive dispensing operations. For example, Pharmacy Tech wages have increased 33% since 2015. 

• ​Shifting Patient Preferences: Consumerism has created expectations of more modern personalized and real time experiences. 

• ​Expanding Clinical Responsibility: 77% of patients now view pharmacists as an integral part of the care team. 

​Pharmacies are an essential element of the healthcare delivery system that promote medication access, safety and adherence while also taking a broader role in care delivery. In the US alone, there are over $7B of prescriptions processed annually, representing >$500B of annual expenditure. Automation unlocks revenue growth and profit margin expansion for pharmacies across all end markets and dispensing formats. BD is the global pharmacy automation leader in high volume packaging and retail dispensing, addressing customers’ most pressing issues in safety and efficiency. The TLDP would have an opportunity to join a rapidly growing R&D team focused on solving some of BD’s most tangible needs in the market with focus on the Vision Portfolio which is seen an area where we can be a market differentiator. 

​​The high-level work plan envisioned for this opportunity would include the following milestones.   

• ​At the beginning is developing a proof of concept of incorporating a data pipeline to manage different datasets, management of datasets, and incorporation of a data pipeline through the development of the proof of concept called VisionWatch. This is an internal tool and application to assist the Vision team under Blister to manage, develop, and track the various datasets for training and validating 

• ​Second component is developing and handing the datasets to the Automation aspect to ensure that the training team can begin training the Deep Learning models based on the images and annotations that have been provide

• The intern has respons