Snorkel is looking to redefine how AI is built by helping enterprises transform expert knowledge into specialized AI at scale, with a focus on building custom AI with their data faster than ever before.
Requirements
Deep experience with AI/ML pipelines, LLM-based systems, or agentic workflows
Experience with distributed computing, large-scale data systems, or orchestration frameworks
Expertise in Python and cloud platforms (AWS, GCP, or Azure)
Strong understanding of production web-scale systems: monitoring, telemetry, reliability, performance, debugging, and triage
Experience designing platforms for machine learning, synthetic data generation, or reinforcement learning environments
Experience with LLM infrastructure, API unification layers, distributed inference, or model-serving systems
Experience with Typescript and React (for platform-oriented or internal tool development)
Responsibilities
Architect the core platform that powers synthetic data generation, agentic workflows, RL environments, and scalable LLM operations
Build distributed systems that allow customers — and our own expert network — to generate datasets and evaluations at unprecedented scale
Design and evolve the APIs, compute services, and orchestration layers that empower internal and customer-facing applications
Collaborate across product, research, and engineering teams to define the long-term technical strategy of Snorkel
Act as a technical leader, mentor, and culture-setter for the engineering organization
Serve as a key advisor to company leadership while owning high-impact, highly ambiguous problem spaces
Think years ahead about where AI is going — and help Snorkel build the infrastructure that gets us there
Other
Bachelor’s degree in Computer Science or related field
12+ years of experience building customer-facing, cloud-native software systems
Experience at high-growth technology startups
Experience building software products for large enterprise customers
Passion for mentorship, technical leadership, and elevating engineering culture
