Sumble

Sumble provides AI-powered account intelligence for enterprise sales teams, helping users understand team structures, reporting lines, tech stacks, and other account signals to drive pipeline.

Technology, Information and Internet
11-50
$38M raised

Description

  • Finetune small language models for data quality and enrichment workflows.
  • Improve the quality of existing data using scalable methods and validation techniques.
  • Verify and correct entity relationships such as company URLs, headquarters addresses, and parent-subsidiary mappings.
  • Add new signals by scrubbing, matching, normalizing, and aligning them to the existing ontology.
  • Push data quality solutions into production and support them in data pipelines and backend systems.
  • Use techniques such as LLM validation, SERP checks, and cross-source triangulation to improve accuracy.
  • Work with growing sets of data sources, machine learning models, and large-scale data operations.
  • Contribute to systems that support efficient analytics and a strong product-led growth experience.

Requirements

  • Must be located within Americas time zones.
  • Experience working with small language models, LLMs, or machine learning-based data workflows is implied by the role.
  • Familiarity with Python and backend or data pipeline environments.
  • Experience with data cleaning, matching, normalization, or ontology mapping is relevant for the role.
  • Knowledge of ML/data tooling such as PyTorch, Hugging Face, Gemma models, LoRA, or vLLM is a plus.
  • Experience with FastAPI, React, Typescript, PostgreSQL, DuckDB, or Google Cloud Platform is a plus.
  • Ability to work on production systems and operational data infrastructure.
  • Experience in environments handling noisy datasets and multiple data sources is a plus.

Benefits

  • Medical, dental, and vision coverage for US employees.
  • 401(k) plan for US employees.
  • Target of 4 weeks of PTO.

Interested in this position?

Apply directly on the company website

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