Summary:

Facebook is seeking a Visiting Professor, RTP Data Analytics to join our Release to Production Engineering (RTP) team. The role will require the application of state-of-the-art data science and machine learning techniques to help improve our cutting edge power and hardware fleet. Our servers and data centers are the foundation upon which our rapidly scaling infrastructure efficiently operates and upon which our innovative services are delivered. We’re looking for someone who can contribute to this effort.We are seeking a Visiting Professor to join us. Individuals in this role are expected to be PhD holding professors who have hands-on experience and can collaborate effectively with partner engineering organizations, fellow data scientists and leadership.The term length would be at least 6 months and the ideal candidate should already have a deep background in statistical and machine learning techniques.As a Visiting Professor, you will need to develop subject matter expertise, build trust with partners, recognize the biggest opportunities, create and drive strategy, and leverage data science methodologies to solve hard problems. In your work, you may provide guidance and coordinate with other data scientists to help achieve the goals in broad areas of operation.

Required Skills:

Visiting Professor, RTP Data Analytics Responsibilities:

1. Proactively create research ideas, experiments, and data analyses to detect and diagnose hardware health/performance issues, focusing on systemic solutions

2. Interface with internal hardware and software engineers and operations teams to understand system architectures and failure modes

3. Share insights with stakeholders and software teams to develop architectures to handle server failures based on hardware health data

4. Develop and deploy machine learning-powered solutions and research directions for hardware sustaining at scale

Minimum Qualifications:

Minimum Qualifications:

5. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

6. Ph.D. in Applied Statistics, Computer Engineering, Computer Science, Electrical & Electronics Engineering, Electrical Engineering, Electrical Engineering and Computer Sciences, Electronics Engineering, Machine Learning, or Mathematics and Statistics 3 or more years of experience with AI/ML related research

7. Troubleshooting and data tooling skills (data analysis, big data, building analytical models, visualizations)

8. Relevant publications in Computer Architecture, High-Performance Computing, Networking Architecture, Reliability and Resilience Conferences

Preferred Qualifications:

Preferred Qualifications:

9. 5 or more years of experience with statistical analysis, statistical hypothesis testing, statistical modeling, or statistics

10. Machine learning/neural network expertise

Public Compensation:

$163,000/year to $225,000/year + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@fb.com.