Applied ML Engineer

🕒 February 25

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 53%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Stealth Startup

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Stealth Startup is a B2B SaaS platform that provides an AI-powered startup discovery and market intelligence engine for investors, growth funds, and corporate development teams. It aggregates proprietary and web data on millions of companies and people, offers search, automated research via an AI agent, Chrome extensions, and developer APIs (REST/GraphQL) to integrate data into workflows. The product helps users discover early signals, monitor traction, generate research reports, and move from insight to outreach without leaving the platform.

📋 Description

• Ship and support AI-native products from concept to production. • Apply sound judgment on building and maintaining high-performing production ML systems. • Stay deeply informed on the latest machine learning research and developments. • Collaborate with a team of strong engineers; serve as a mentor and resource for other high-potential ML engineers.

🎯 Requirements

• 5+ years of experience in delivering and supporting production AI/ML products. • An advanced degree in Machine Learning, Theoretical Computer Science, Mathematics, or Physics, or equivalent experience evidenced by meaningful contributions to open-source AI/ML projects or the creation of successful AI products. • Excellent decision-making skills regarding large-scale ML system design and maintenance. • Strong awareness of current trends and progress in machine learning research. • A drive to want to work with and learn from, eager to help shape a high-caliber engineering team. • A proven track record with companies known for strong engineering cultures, including meaningful startup experience.