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JFrog

Artifact repository and supply chain security

Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A Master of Science in computer science or an equivalent quantitative field, such as Mathematics, Statistics, Engineering, or Economics, with a focus on Machine Learning.
  • At least 5 years of industry experience in data science or machine learning roles, including developing machine learning models from initiation to production.
  • Strong foundations in data science and machine learning, including evaluating model outputs and performance.
  • Ability to investigate problems using messy, ambiguous, or incomplete data and communicate results clearly and efficiently.
  • Hands-on proficiency with the Python machine learning and deep learning ecosystem.
  • Hands-on experience implementing and evaluating custom retrieval-augmented generation (RAG) systems, understanding their operation and performance evaluation, and improving them.
  • Ability to serve as a technical expert for RAG and complex agentic workflows such as deep research and wide search, with near-complete recall, high precision, high scale, low latency, and low cost.
  • Hands-on proficiency with databases.
  • Experience in time-series forecasting.
  • Ability to work independently and deliver results.
  • Ability to manage relationships with key partners across different functions and collaborate effectively with remote teams.
  • Excellent spoken and written English.

Responsibilities

  • Listen to business stakeholders, understand their challenges, and propose data-driven solutions using machine learning models and advanced statistical methods, such as classifiers for rare events that trigger business action or time-series predictors in noisy environments that affect business planning.
  • Work alongside business units to gather requirements, collaborate with cross-functional teams, iterate on data research, and deliver solutions to production.
  • Own the full lifecycle of machine learning models, monitor existing models, and continuously improve the data science automation pipeline.
  • Rapidly prototype ideas, such as custom retrieval-augmented generation solutions, agentic processes, and knowledge graphs, based on applied research or academic concepts, and productionize successful prototypes.
  • Contribute primarily to the semantic engine component of the organizational brain platform and serve as a technical authority in that domain.
  • Identify opportunities for improvement and innovation with business impact, and develop high-quality ideas.
  • Contribute as an independent individual contributor and communicate effectively in writing and verbally.

About the Company

JFrog

Artifact repository and supply chain security

JFrog provides an end-to-end platform for managing and securing the software supply chain, with Artifactory serving as a universal repository for binaries, packages, and containers. Developers use the platform to automate builds, store artifacts, and feed CI/CD pipelines, with support for cloud or on-premises deployments and built-in security features. It differentiates itself by offering a single, universal repository that handles many package types and integrates with DevSecOps tools, plus a free open-source Artifactory option and enterprise-grade subscriptions. The goal is to help organizations securely automate and scale software delivery through centralized artifact management and continuous software supply-chain security.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
2008

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