Senior Software Engineer — AI/ML

Posted 2 Days Ago
Easy Apply
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2 Locations
In-Office
200K-250K Annually
Senior level
Artificial Intelligence • Machine Learning
The Role
As a Senior Software Engineer, you will build large-scale AI systems, work on distributed computing, and enhance AI capabilities with advanced technologies.
Summary Generated by Built In

About Snorkel

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 Software Engineer on the Evaluation Engineering team, you'll build systems to power large-scale AI workloads for top tier AI research labs. You’ll work closely with other engineers, product managers, and field team members to ensure that Snorkel’s frontier AI datasets meet and surpass the capabilities of the most advanced foundation models. You will launch agents into production to accomplish long running reasoning and verification tasks. The Evaluation Engineering team owns critical systems for building high quality post-training and benchmark datasets, integrating with the latest foundation model technology to push the frontier of models used globally across coding, mathematics, law, medicine, and other advanced domains.

Main Responsibilities
  • Own the architecture, design, development, and operations of large-scale systems designed for AI/ML tasks including distributed compute systems, data management systems, data engineering workflow systems, and end user experiences
  • Recognize and act on opportunities to integrate the latest agentic and foundation model technologies to power eval workflows
  • Prototype, optimize, and maintain scalable back-end services that will power new foundation model development tools
  • Design extensible and testable interfaces between internal services including the underlying storage and data models
  • Be an engaged team player in a customer-focused cross-functional environment where you will feel excited to take on whatever is most impactful for the company and product
  • Work a hybrid schedule with 3 days per week in one of our offices in San Francisco or Redwood City
Required Qualifications
  • 4+ years experience in delivering AI/ML systems and services in a production setting for cloud-native applications
  • Experience with distributed compute frameworks
  • Experience with the modern AI stack, including improving LLM applications through evals, prompting, and agent scaffolding
  • Ability to design and build efficient data storage, compute, and retrieval systems for AI/ML tasks
  • Strong communication and coding skills with emphasis on designing for scale and robustness
  • Experience owning the delivery of large multi-person projects
Preferred Qualifications
  • 8+ years of professional software engineering experience
  • Experience with architecting and developing production web-scale systems (monitoring, telemetry, performance, reliability, triage and debug)
  • Strong development and debugging skills in Python
  • Experience with expert data annotation projects
  • Experience developing evaluations and environments for complex multi-turn and multi-tool AI systems

Salary Range
$200,000$250,000 USD

Be Your Best at Snorkel

Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.

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

Cloud-Native Applications
Distributed Compute Frameworks
Python
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The Company
HQ: Redwood City, CA
120 Employees
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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