Sei

LLM Engineer

Sei
3.6 / 5
Chennai Not disclosed
Last week
On-Site
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About the job

What to expect You can expect to do all of the following: • Orchestrate workflows across closed and open source models • Build pipelines to clean and transform data for RAG • Evaluate multiple models for text classification, sentiment analysis, STT, etc. on multiple rubrics • Create and run evals • Clean, prune, and collect datasets to analyze model performance, hallucination rates, recall, etc. • Research and implement SOTA approaches for knowledge graphs and Graph RAGs • Implement inference-time reasoning approaches to improve the accuracy of models Our values • Continuous 360 feedback: Everyone is expected to share constructive, critical feedback with everyone else, including the founders. • Product-minded: Everyone shares product ownership, so we expect everyone to engage in customer outreach, support, and customer conversations to gather feedback and identify new features. • Doers over talkers: We spend time figuring out the right direction, then execute quickly. No one is too “senior” to do a job - the CTO will code every day, the CEO will sell every day, and everyone takes care of customer support on a schedule. We understand the difference between real work and pretense. • Humanity over everything else: We sell the product to businesses, but in reality, we sell it to real humans on the other side. Our end customers are consumers using the product through our UI or integrated with our APIs, so we are building the world’s most human-centric company (no pun intended). Kindness is expected, and empathy is the core value we’re looking for.

Requirements

  • AI/ML
  • LLM
  • Data Pipelines

Qualifications

  • Experience with AI/ML and LLMs

Preferred Technologies

  • AI/ML
  • LLM
  • Data Pipelines

About the company

Sei is an innovative agentic AI platform aiming to enhance the financial services industry. Backed by top investors and an experienced team, Sei focuses on scalable and robust tech solutions to meet the growing demands of its enterprise customers.

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