Senior Backend Software Engineer; West, Remote or Hybrid

Opportunity

In this role, you will make a real impact on the safety of large language models and generative AI solutions across different verticals. You will work on the cutting edge of envisioning and building new types of tools and algorithms to monitor, explain, and improve such models.

• Design and build a world‑class cloud platform to help enterprises monitor and analyze their ML models, covering both predictive models as well as LLM and generative models
• Design enterprise‑grade, scalable APIs and frameworks to run analysis and validation of customers’ ML models and workflows
• Develop new types of metrics and evaluation methods for quality and robustness of ML models
• Work with product and customer‑facing teams to enhance and expand our product
• Recommend and implement engineering best practices, improve the functionality of existing software, and ensure that the design, application, and maintenance of software meets quality standards

• BS/MS/PhD in Computer Science or equivalent
• 3-4 years of experience
• Proficiency with Python
• Experience working with ML models in production; familiarity with common LLM frameworks (Langchain, Llamaindex, RAG, Hugging Face) and evaluation frameworks (Ragas, Presidio)
• Experience debugging and troubleshooting production systems, on‑call support experience
• Experience working with common distributed systems infrastructure:
  Redis, Postgres, RabbitMQ, Celery, Flask
• Nice to have:
  Knowledge of infrastructure management (AWS / Google Cloud, Kubernetes, or equivalent on‑premises technologies)
• Nice to have:
  Experience building large‑scale distributed systems and working with columnar and vector databases
• Preferably hybrid with at least 1 day a week in the Palo Alto office; full remote is considered for a strong West Coast candidate

Pay Range in San Francisco California is $130,000 - $190,000

The posted range represents the expected salary range for this job requisition and does not include any other potential components of the compensation package, benefits, and perks previously outlined. Ultimately, in determining pay, we'll consider your experience, leveling, location, and other job‑related factors.