Eragon — Member of Technical Staff
$250,000–$450,000 year
On-siteSan Francisco, California, United States
Job Summary
Build, integrate, and deploy AI-powered systems into production across enterprise customers while fine-tuning and evaluating ML models for real-world applications. Design scalable pipelines for training, inference, and data processing to optimize latency, throughput, cost efficiency, and reliability. Partner with product, research, and design teams to ship end-to-end features, implementing evaluation frameworks and feedback loops. Work with large-scale datasets and internal APIs across customer stacks using Python, modern ML frameworks, and cloud infrastructure. Take ownership of ideas from concept to production without a predefined roadmap in a high-intensity, fully on-site environment in San Francisco.
Required Qualifications
- Bachelor's or Master's in Computer Science, Engineering, or related field
- Strong proficiency in Python and modern engineering or ML frameworks
- Experience building and deploying systems in production environments
- Familiarity with data pipelines, APIs, and cloud infrastructure (AWS, GCP)
- Experience working with machine learning models or data-driven systems
- Must be able to handle everything from modeling to systems to product, taking ideas from concept to real-world production without a roadmap
- Must be fully on-site in SF
- Must be willing to match the intensity of the culture
- Must have built something meaningfully and owned it in production
Desired Qualifications
- Experience deploying or scaling ML systems in production
- Familiarity with LLMs, agents, or workflow automation systems
- Experience with distributed systems or large-scale infrastructure
- Prior startup experience as a founding team member or co-founder, has operated without structure and thrived
- High-growth startup background from Databricks, Stripe, Ramp, or equivalent with a compelling reason for pivoting into a heavy AI role
- Background at a frontier AI lab, Anthropic, OpenAI, DeepMind, or equivalent, signals the technical depth and AI-forward mindset
- Has lived and worked in the SF Bay Area or a comparable major startup ecosystem and understands the culture
- Top school pedigree: MIT, Stanford, Berkeley, CMU, Waterloo, or equivalent
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