Senior Software Engineer - Expert Contributor Lifecycle

Snorkel AI•Redwood City, CA

7h•Hybrid

About The Position

At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, 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! As a Senior Backend Engineer at Snorkel, you will deliver robust features that power our Expert Contributor (EC) Platform. You will have full ownership and responsibility for building, shipping, and maintaining innovative, scalable services and complex features as well as building and maintaining integrations with various vendors. Your work will bridge the gap between human expertise and machine learning by enabling domain experts to provide high-signal data for training and refining state-of-the-art models.

Requirements

8+ years of software engineering experience, including deep ownership of build, test, or CI/CD systems.
6+ years of professional experience developing performant, intuitive, and scalable web application architectures.
Strong background in developer productivity, distributed systems, and cloud platforms (AWS preferred).
Expertise designing REST for internal services and developers.
Proven experience owning and evolving CI/CD systems for large-scale codebases, focusing on reliability, scalability, and developer productivity.
Experience developing and shipping enterprise software products, specifically those focused on data collection, annotation, or machine learning applications.
Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact.
Comfortable working with: Infra & deployment technologies: Terraform, Docker, Kubernetes. CI/CD systems: CircleCI, Buildkite, GitHub Actions, Helm.
Ability to work in a fast-paced environment with strong technical communication skills.
Self-motivation, a positive mental attitude, and an eagerness to learn in the rapidly evolving AI landscape.

Nice To Haves

Experience in hyper-growth startup environments or scaling engineering orgs.
Experience with AI development workflows, AI-assisted code generation, or SRE automation or strong excitement to learn.
Prior experience as a Tech Lead, Team Lead, or Hands on Engineering Manager.

Responsibilities

Design and develop mission-critical systems for the end-to-end Expert Contributor (EC) lifecycle, focusing on automated onboarding workflows, performance management, and contributor retention.
Build robust features and integrations with key third-party services, including platforms for assessments and Employer of Record systems.
Automate supply and allocation logic to efficiently manage and deploy a high volume of ECs to various data collection projects, ensuring optimal coverage and quality.
Prototype, optimize, and maintain scalable services to power complex data user management pipelines.
Set the strategy and architecture for build systems, testing frameworks, and CI/CD pipelines.
Lead the transition from scheduled releases to a robust, automated continuous deployment framework, taking end-to-end ownership of the release pipeline.
Build proactively with empathy for both customers and subject matter experts using our tools.
Collaborate with engineers to bring consistency and high standards to codebases, infrastructure, and processes.
Partner with cross-functional teams to design and deliver improvements to dev-infra, release processes, and internal tooling.
Engage with product managers, designers, and ML experts to create a phenomenal user experience for data acquisition and refinement.