SENIOR COMPUTER SPECIALIST - MACHINE LEARNING

As a UW employee, you have a unique opportunity to change lives on our campuses, in our state and around the world. UW employees offer their boundless energy, creative problem-solving skills and dedication to build stronger minds and a healthier world.

UW faculty and staff also enjoy outstanding benefits, professional growth opportunities and unique resources in an environment noted for diversity, intellectual excitement, artistic pursuits and natural beauty.

This position requires demonstrable technical proficiency in signal detection in the acoustic/spectrogram domain, and experience with applying best practices in the field of acoustic data analysis. The position requires a high level of domain knowledge including background knowledge in the calling repertoire of species in the region and their spatiotemporal distribution necessary to strategize Machine Learning (ML) development. This position also requires familiarity in computer science and software development- the domain is relatively unexplored in terms of enterprise software, so basic capabilities in the AI/ML lifecycle are require for the development of custom software. Additionally, advanced computer science principles are necessary to ensure ML techniques fit goals for operationalization in an environment of limited data storage, GPU compute, and federal security policy. Senior Computer Specialist will be responsible for advocating for internal operational funding, and make recommendations for software and operational objectives.

The ML Senior Computer Specialist will develop and apply machine learning (NL) techniques to support acoustic monitoring of marine mammal species in the Alaska Region. Successful software approaches will satisfy components for performance, speed, low operational complexity, and low barrier to entry for non-technical staff. ML techniques could include a wide variety of machine learning approaches and frameworks, but current best practices generally use an imagery domain (spectrogram ) detection/classification approach, and sensorflow/pytorch are commonly useful frameworks for this. In addition to machine learning techniques, the engineer will need to incorporate necessary signal processing and data management paradigms in a performant and scalable manner. Downstream products of the software (labeled acoustic detection of species) will be used to support research in a few ways. One way is to streamline existing monitoring approaches, which require the ML approach to be performant at a low granularity, while more future looking applications such as calling behavior and density estimation would require strong performance at a higher granularity.

DUTIES AND RESPONSIBILITIES

1. Research, identify, and adapt appropriate and performant ML techniques for utilization (5%)

2. Software and ML development and integration of proof of concept and existing ML technique into end product modularized software packages, and documentation/publication of software approaches (75%)

3. Provide guidance in the utilization of the developed software (including activities of analyst staff) towards operationalization of these techniques for streamlined acoustic monitoring of relevant species (20%).

MINIMUM REQUIREMENTS
• Bachelor's Degree in STEM or related field
• 3+ years of job-related experience

Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.

ADDITIONAL REQUIREMENTS
• Acoustic data analysis
• Software development and scripting (Python, R, MATLAB)
• ML pipeline development
• ML framework development
• Operationalization
• Computer science
• Literature review
• Research and scientific writing
• Project management
• AI/ML operationalization

Application Process: The application process may include completion of a variety of online assessments to obtain additional information that will be used in the evaluation process. These assessments may include Work Authorization, Cover Letter and/or others. Any assessments that you need to complete will appear on your screen as soon as you select "Apply to this position". Once you begin an assessment, it must be completed at that time; if you do not complete the assessment, you will be prompted to do so the next time you log into your "My Jobs" page. If you choose to take it later, it will appear on your "My Jobs" page to take when you are ready. Please note that your application will not be reviewed, and you will not be considered for this position until all required assessments have been completed.

Committed to attracting and retaining a diverse staff, the University of Washington will honor your experiences, perspectives and unique identity. Together, our community strives to create and maintain working and learning environments that are inclusive, equitable and welcoming.

The University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, protected veteran or disabled status, or genetic information.

To request disability accommodation in the application process, contact the Disability Services Office at [redacted] or [redacted].

Applicants considered for this position will be required to disclose if they are the subject of any substantiated findings or current investigations related to sexual misconduct at their current employment and past employment. Disclosure is required under Washington state law.