Engineering Manager—Operations

Posted 9 Hours Ago
Be an Early Applicant
2 Locations
Senior level
Artificial Intelligence • Machine Learning
The Role
The Engineering Manager—Operations will lead and grow a team responsible for automation and tooling around data workflows and analytics. The role involves collaborating with operations, engineering, and product teams to implement systems that support company growth, providing mentorship, and fostering a strong engineering culture.
Summary Generated by Built In

We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

We are looking for the founding Engineering lead for our Operations Engineering team. This team is responsible for redefining how the world’s largest organizations meet their data annotation needs for groundbreaking models. 

You’ll define and grow a team building automation and tooling around data generation, dataset analytics, quality checks. The automation and tooling directly supports our fast-growing Data-as-a-service (Daas) operations and are used as feedback to incorporate into Snorkel’s core programmatic data development platform. You’ll work closely with cross-functional teams incorporating research, applications engineering, and operations to pioneer innovative workflows for best-in-class ML models.

Primary responsibilities

  • Manage, develop, and grow a talented team of operations, automation, data, and infrastructure engineers
  • Work with the rest of our operations, product, engineering and research teams to help design and lead the implementation of our internal and external systems to support the growth of the company
  • Actively contribute to Snorkel’s engineering culture through mentorship, open communication, user empathy, advocacy of strong engineering practices, and more

Preferred qualifications

Successful candidates will have most of the following, but these should be viewed as guidelines, not hard requirements:

  • Degree in Computer Science or related field or equivalent experience
  • 5+ years of professional experience developing systems and process for software operations and development
  • 3+ years of engineering management experience
  • Experience with architecting and developing systems to operate data workflows and pipelines, content analytics, or user reputation and fraud analytics
  • Experience at high-growth technology startups, and balancing ambiguity and agility with rigor and sustainability
  • Familiarity with ops and devops systems and processes
  • Experience developing and mentoring engineers
  • Background managing, building on, and deploying with AWS, Terraform, Kubernetes, SQL 

Be Your Best At Snorkel

 

Snorkel AI is on a mission to make machine learning practical for everyone, and it starts with building a team that welcomes, represents and gives opportunity to all. We work at the frontier of AI and software engineering, and believe that underrepresented communities need to play a part in shaping the future of these fields. At Snorkel AI, we actively work to create an environment that values end-to-end ownership, diverse forms of impact, and opportunities for personal growth.

 

Snorkelers are supported by an amazing team and an amazing set of benefits. For Full-time employees, we offer comprehensive medical, dental, and vision plans for Snorkelers and their families, plus a yearly wellness stipend. Our 401k program lets Snorkelers plan for their future and our parental leave program lets new parents take up to 20 weeks of paid time off. Learn more about these benefits and more — like our workstation setup allowance — on our Careers page.

 

Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.

 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Top Skills

AWS
Kubernetes
SQL
Terraform
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The Company
HQ: Redwood City, CA
120 Employees
Hybrid Workplace
Year Founded: 2019

What We Do

Our mission is to empower everyone to solve their most impactful problems through data-centric AI. To do this, we have introduced Snorkel Flow, a data-centric AI platform, and are building an incredibly talented team. We empower Fortune 500 enterprises such as Chubb and BNY Mellon, and several government agencies to accelerate AI application development by 10-100x.

Why Work With Us

The founding team spent over half a decade researching programmatic labeling, weak supervision, and other techniques to break through one of the biggest bottlenecks in AI: the lack of labeled training data. This research has resulted in Snorkel research project and 60+ peer-reviewed publications. Snorkel has developed and deployed its technology

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