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). As a Postdoc Appointee in Machine Learning and Software Engineering, you will be expected to develop and deploy machine learning techniques at scale across a range of Vail business verticals. You would research the fields of machine learning, machine learning operations (MLOps), software engineering, and software-intensive systems in industrial settings. In this role, you would work with your project mentors to publish your postdoc work to top tier venues and conferences.
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 and act as a mentor to the RAILS PhD Data Science summer intern. Additionally, the candidate will be an informal mentor, detail-oriented, and eager to learn.
What you’ll do:
- Use social network analysis to characterize collaboration between software development teams
- Identify and classify software engineering challenges when developing software-intensive systems that incorporate machine learning components
- Machine learning-based analysis of program binaries
- Automated software vulnerability analysis and testing using deep 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
- Log analysis and insight extraction
- 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
- Use machine learning to predict software defects
- A PhD in Computer Science, Data Science, Mathematics, Human-Computer Interaction, or Natural Language Processing, Computational Linguistics or are currently enrolled in a full time, relevant, degree program at an accredited University/College and will have your most recent degree completed by the start of the postdoc
- Experience developing in 1+ scripting language, such as Python or R
- Passion for leveraging expertise from computer science and/or other technical fields to solve real-world challenges through applications of machine learning
- Experience working collaboratively in a highly technical environment
- Enthusiasm for industry research
- Excellent verbal and written communication skills
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.
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.