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Sumble

Sumble

via Talents By Vaia

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Data Scientist/Machine Learning Engineer

Anywhere
Full-time
Posted 3/11/2026
Verified Source
Key Skills:
PyTorch
Machine Learning
Data Pipelines

Compensation

Salary Range

$70K - 120K a year

Responsibilities

Fine-tune language models, improve data quality, add new data signals, and deploy solutions to production.

Requirements

Experience with ML models, data processing, Python, and working within Americas timezones.

Full Description

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

This job posting was last updated on 3/11/2026

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