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Data Scientist/Machine Learning Engineer

sumble-inc

USremote countryPosted Aug 31, 2025

At a glance

Highlights

  • Remote work within Americas timezones
  • Early‑stage product with strong market fit
  • Team of ex‑Google/Meta engineers

Why this role might suit you

The role offers a chance to apply cutting‑edge LLM techniques to real‑world data challenges, collaborating with a small, high‑caliber team while working remotely across the Americas.

Skills

pytorchhuggingfacegemmaloravllmskypilotmarimopythonfastapireacttypescriptgcppostgresqlduckdbcloud-runfigmavercel

About the role

Sumble is building a knowledge graph from web data with a first focus on data for go-to-market teams. We use sources like job posts and resume data to identify things like org structure, tech stack, and key projects (e.g., GenAI initiatives, cloud migrations). Our product already has strong product-market fit, early revenue, and happy customers — and now we’re ready to accelerate.

Our long-term vision is to become the primary destination for accessing high-quality web data. Try the product at sumble.com.

Our Team: We are a team of 15, including 10 engineers with experience at companies such as Google, Meta, Stack Overflow, and Kaggle.

What you'll do

Finetuning small language models

Improving the quality of existing data using scalable approaches. Examples include: making sure URLs are associated the right company, we have the correct HQ address, we have mapped parents-subsidiary using techniques like LLM validation, SERP, and triangulating across sources.

Adding new signals: this usually involves scrubbing, matching and normalizing new signals and matching to our existing ontology

Pushing solutions into production environments, which may involve touching data pipelines and/or backend systems

Requirements

Located within Americas timezones

More about Sumble

Our Tech Stack:

ML/Data: PyTorch, Huggingface, Gemma models, LORA, VLLM, Skypilot, Marimo

Languages & Frameworks: Python, FastAPI, React, Typescript

Cloud Platform: Google Cloud Platform (GCP)

Databases: PostgreSQL, DuckDB

Infrastructure: Cloud Run

Product/Design: Figma, Vercel V0

Challenges We Tackle:

Transforming noisy datasets into high-quality data products

Running expensive analytics computations efficiently

Managing the complexity of a growing number of data sources, machine learning models, and large data operations

Create a great PLG experience with upsell pathways

Benefits

Medical, dental, and vision (US)

401k (US)

Target 4 weeks PTO

Questions about this role

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