Staff Machine Learning Engineer

Staff Machine Learning Engineer

This job is no longer open

We are interviewing and onboarding 100% virtually at this time. PagerDuty is focused on inclusion and employee well-being by building a culture that isn’t location specific and gives equal opportunity to everyone—regardless of where you are working. Unless your job requirements make it necessary to be in a company office, you may choose to work in-office, remotely, or hybrid.

Why We Need You:

We’re looking for a staff-level engineer and a proven technical leader passionate about successfully collaborating with data scientists and engineers to run machine learning models in production. We expect you to understand requirements from the data science and data engineering team and drive alignment with Engineering teams on design patterns and best practices to support the business.

You are expected to anticipate data science & engineering-related bottlenecks, suggest escalation and investment wherever necessary, communicate immediate and long-term technical as well as strategic solutions and trade-offs, and will possess an excellent capacity to manage time. In addition, you will demonstrate emotional intelligence as you navigate stakeholder relationships championing the organization's data science and machine learning initiatives.

How you contribute to our vision: Key Responsibilities

  • Build and improve the capabilities of the data platform that enable and accelerate the production of machine learning (ML) based solutions
  • Drive and define standards for data engineering across the organization. 
  • Provide guidance, technical leadership, and mentoring to other members of the team
  • Proactively recommend improvements and new approaches addressing potential systemic pain points and technical debt
  • Anticipate technical demands on the data platform based on the organization’s roadmap and systematically drive the evolution of the architecture towards those ends
  • Mentor junior members and participate in scaling up the existing team 
  • Develop a long-term plan for data science investments 

Minimum Requirements

  • You have 8+ years of experience building, designing, and evolving data architecture for large-scale systems 
  • Experience working with Product teams ensuring and driving a timely delivery
  • Have a deep understanding of the trade-offs to be considered when designing and delivering machine learning solutions to production
  • Demonstrated experience with data modeling, database design, extract transform load (ETL) processes, working with unstructured data, and cloud-based data infrastructure
  • Awareness of and experience with ML processes (exploration, training, deployment), technologies (services, packages), and infrastructure (AWS)
  • Passionate about data/ML engineering and interested in driving discussions with stakeholders and executives




Not sure if you qualify?

Apply anyway! We extend opportunities to a broad array of candidates, including those with diverse workplace experiences and backgrounds. Whether you're new to the corporate world, returning to work after a gap in employment, or simply looking to transition or take the next step in your career path, we are excited to connect with you.

PagerDuty Offers

We are dedicated to providing a culture where our people are happy, enabled and inspired to do their best. One of the ways we do this is by developing a comprehensive total rewards approach that supports employees and their loved ones. As a global organization, our programs are competitive with industry standards and aligned with local laws and regulations. 

Your package may include:

  • Competitive salary and company equity
  • Comprehensive benefits package from day one
  • ESPP (Employee Stock Purchase Program)
  • Retirement or pension plan
  • Paid parental leave - up to 22 weeks for pregnant parent, up to 12 weeks for non-pregnant parent (some countries have longer leave standards and we comply with local laws)
  • Generous paid vacation time 
  • Paid holidays and sick leave
  • Paid employee volunteer time - 20 hours per year
  • Bi-annual company-wide hack weeks
  • Mental wellness programs
  • Dutonian Wellness Days - scheduled company-wide paid days off in addition to PTO and scheduled holidays
  • HibernationDuty - a week each year when everyone at PagerDuty, with the exception of a small, coverage crew, is asked to take a much needed break to truly disconnect and recharge

About PagerDuty

PagerDuty, Inc. (NYSE:PD) is a global leader in digital operations management, serving over 14,000 customers and 850,000 users worldwide, including 65% of the Fortune 100.

For the teams who build and run digital systems, PagerDuty is the best way to manage the urgent, mission-critical work that is essential to keeping digital services always on. We make it easy to handle any unplanned task, event, or opportunity, right away.

Led by CEO Jennifer Tejada, 50% of our board of directors is comprised of women, 45% of our managers are from underrepresented groups, and we are a proud member of the Pledge 1% Movement, committed to donating 1% Equity, 1% Employee time, and 1% Product to accelerate change in our communities. We are Great Place to Work-certified™ and our product is top rated in its category on TrustRadius.

From how we build our teams to who sits in the boardroom, we hope you can see yourself at PagerDuty.

Learn more: Social Impact; Inclusion, Diversity, & Equity; Culture

Additional Information

PagerDuty is committed to creating a diverse environment and is an equal opportunity employer. PagerDuty does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, parental status, veteran status, or disability status.

PagerDuty is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application process. Should you require accommodation, please email accommodation@pagerduty.com and we will work with you to meet your accessibility needs.

PagerDuty verifies work authorization in accordance with the requirements of your local jurisdiction.

This job is no longer open
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