Software Engineer — AI Platform

Sorry, this job was removed at 12:12 a.m. (CST) on Friday, May 16, 2025
2 Locations
In-Office
Artificial Intelligence • Machine Learning
The Role

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!

As an AI Platform Engineer, you will be at the forefront of designing and implementing the core AI pipelines that drive SnorkelFlow’s AI capabilities. Whether you’re an entry-level engineer eager to grow in the field or a senior engineer ready to lead high-impact projects, this role offers opportunities to work on SOTA AI models and redefine the AI stack through a data-driven primary way to solve challenging problems.

Main Responsibilities
  1. AI Pipeline Development:
    • Contribute to designing and maintaining AI pipelines for labeling, embeddings, training, and deploying models into production.
    • Collaborate with the Compute Platform team to ensure seamless integration with orchestration tools and infrastructure.
    • Define and develop AI Platform APIs for other applications to use them
  2. LLM Tooling Development:
    • Build and deploy LLM-based systems for production workflows, focusing on efficiency, scalability, and reproducibility.
    • Implement training pipelines for LLMs, including fine-tuning, pruning, distillation, and foundational model training.
    • Integrate APIs from providers such as OpenAI, Anthropic, and Gemini into SnorkelFlow’s pipelines.
  3. Backend Development:
    • Develop and integrate backend services to manage LLM calls and API interactions.
    • Work with the Data Platform team to define data requirements and ensure smooth interoperability.
    • Partner with the Application team to design and implement APIs that power workflows.
  4. Observability and Monitoring:
    • Implement tools and dashboards to monitor and track AI pipeline performance.
    • Define metrics to ensure system health and support optimization efforts.
  5. Advanced Model Development:
    • Innovate on advanced training methodologies for LLMs and NLP systems, including state-of-the-art optimization techniques.
    • Take ownership of end-to-end model lifecycle management, from training to production deployment.
Required QualificationsEntry-Level Engineers:
  • Bachelor’s degree in Computer Science, Machine Learning, or a related field.
  • 1-2 years of experience in AI development or backend engineering.
  • Strong coding skills in Python and familiarity with deep learning frameworks like PyTorch or TensorFlow.
  • Passion for AI development and willingness to learn advanced techniques.
Senior Engineers:
  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field.
  • 4-6 years of experience in A and or backend development, including hands-on work with AI pipelines in production systems.
  • Strong expertise in Python and deep learning frameworks such as PyTorch.
  • Proven ability to lead projects and mentor team members.
  • Solid understanding of LLM architectures, fine-tuning, and deployment.
  • Solid understanding of agentic workflows and tooling (Langchain, Crew.ai etc)
  • Experience building scalable CI/CD pipelines for machine learning workflows.
Preferred Qualifications
  • Expertise in NLP and libraries such as Hugging Face Transformers, spaCy, or XGBoost.
  • Familiarity with multimodal AI concepts, including vision and audio tasks.
  • Knowledge of foundational model APIs such as OpenAI, Anthropic, or Gemini.
  • Familiarity with MLOps tools and practices like MLflow, Kubernetes, or Ray.
  • Experience building APIs or SDKs for AI services.
What We Offer
  • A leadership role with the opportunity to influence the technical direction of SnorkelFlow.
  • Competitive salary and benefits tailored to your experience.
  • Hybrid work environment with 3 days per week at our Redwood City HQ and SF Office.
  • "No Meeting" Tuesdays and Thursdays to focus on deep work.
  • The chance to work on cutting-edge infrastructure and drive impactful change in an innovative, fast-paced environment.

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.

Snorkel AI Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Snorkel AI and has not been reviewed or approved by Snorkel AI.

  • Healthcare Strength Comprehensive medical, dental, and vision plans cover employees and dependents, with disability and life insurance included. A yearly wellness stipend supplements core health coverage.
  • Leave & Time Off Breadth Unlimited vacation, paid holidays, and paid sick days are offered. Company-wide rest days are also referenced, expanding time-off support.
  • Parental & Family Support Parental leave for birthing and non-birthing parents and childcare benefits are provided. Flexible work arrangements and remote-friendly perks further support family needs.

Snorkel AI Insights

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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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