TL;DR

Principal Applied Science Manager (AI): Designing and developing the next generation of big data and AI-driven capabilities with an accent on strategic impact, model inference optimization, and applying advanced machine learning techniques to solve complex problems. Focus on E2E solution design, driving projects from concept to production, and upholding scientific rigor in problem-solving.

Location: Onsite in Redmond, United States. Employees within a 50-mile commute of a designated Microsoft office in the U.S. are expected to work from the office at least four days per week.

Salary: USD $139,900 – $274,800 per year

Company

%hirify_global% is redefining what’s possible with data and AI, empowering every person and organization on the planet to achieve more.

What you will do

Drive strategic impact by identifying and leading high-leverage data science and analytics initiatives.
Drive model inference optimization and system integration to reduce cost, latency, and system optimization.
Apply advanced statistical modeling, machine learning, and analytics techniques to tackle complex problems.
Design E2E solutions and drive projects from concept to production in a fast-paced, dynamic environment.

Requirements

Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience.
OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience.
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience.
1+ year(s) of people management experience.
Ability to meet Microsoft, customer, and/or government security screening requirements.

Nice to have

3+ years of people management experience.
3+ years of experience in statistics, machine learning, including deep learning, NLP, econometrics.
Experience moving applied research into shipped product features.
Experience in structuring unscoped problems, defining success metrics, and driving execution under uncertainty.
Analytical mindset with a data-driven approach and high standards of scientific rigor.

Culture & Benefits

A growth mindset, innovation, and collaboration to realize shared goals.
Culture of inclusion built on values of respect, integrity, and accountability.
Opportunities to solve real-world problems at scale with massive datasets and advanced machine learning.