Postdoc Appointee: Machine Learning & Software Engineering
Postdoc Appointee: Machine Learning & Software Engineering
Vail Systems is seeking a Postdoctoral Appointee in Machine Learning and Software Engineering familiar with vision and natural language processing (NLP). The Postdoc Appointee in Machine Learning and Software Engineering will be expected to develop and deploy machine learning techniques at scale across a range of Vail business verticals. The candidate will conduct research at the intersection of machine learning and software engineering, including machine learning operations (MLOps), and software-intensive systems in industrial settings.
The ideal candidate will have knowledge of machine learning systems, machine learning pipelines, deep learning methods, artificial intelligence (AI), automation, software development, research best practices, and writing technical papers to contribute to the growing body of published research from Vail's Research on AI in Linguistics and Systems (RAILS) Team. The candidate will also mentor the RAILS PhD Data Science summer interns, and collaboratively work with the RAILS Team to publish the postdoc work in top tier conferences and journals.
What you'll do:
- Identify machine learning algorithms that aid in solving essential difficulties in the development of software-intensive systems.
- Machine learning-based analysis of programs and applications.
- Automated software vulnerability analysis and testing using learning methods.
- Machine learning operations (MLOps): Issues in deploying and maintaining machine learning systems in production reliably and efficiently. Considerations include scalable machine learning pipelines, concept drift, model and data versioning, model and data validation, monitoring, and integration with visualization systems.
- Software engineering fault analysis: Explore AI/ML techniques to aid in automated test case design, test-case prioritization, and creating oracles for mobile applications and web services to automatically generate test cases.
- Proficient in social network analysis to characterize collaboration between software development teams.
- Use machine learning to predict software defects and costs, and increase software quality and reliability.
Minimum qualifications:
- An earned PhD in Computer Science with emphasis on machine learning and software engineering, or current enrollment in a full time, relevant, degree program at an accredited University/College with plans to complete the degree by the start of the postdoc.
- Experienced Python or R developer.
- Passion for leveraging expertise from computer science and/or other technical fields to solve real-world challenges through applications of machine learning and software engineering.
- Experience working collaboratively in a highly technical environment.
- Excellent verbal and written communication skills.
About Us
The human voice is capable of conveying nuances and meaning that just can't be expressed through clicks and text messages. And for that reason, voice interactions have always had a special power to shape your perception and experiences. At Vail, we believe in the unique power of voice interactions to create more expressive, more intimate, and more efficient interpersonal interactions. Our experts work with Fortune 500 companies to help them serve their customers more efficiently and effectively through the use of various voice technologies. From basic network services, to state-of-the-art IP telephony, to cutting edge real-time analytics, Vail technology makes millions of voice interactions better every day.
Organizational Culture
At Vail Systems we strive to cultivate a supportive culture of continuous learning where employees are encouraged to achieve both personal and team goals by providing innovative telephony solutions that enhance customer contact center experiences. We entrust our employees to work autonomously and also encourage contribution to the decision-making process in a highly collaborative environment where open communication is fostered among teams. Product development is centered around the end user to ensure Vail's products are efficient, productive and add value for our clients.