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This listing was closed on Jul 17, 2026.
Browse Open JobsApplied ML Engineer
Summary by AIEngineer.careers
Applied ML Engineer is a AI Engineer role (full-time). with adaption. in SAN FRANCISCO, US. Imported listing (source: monster.com). Apply on the employer's site (monster.com).
Imported listing (source: monster.com) · Apply on monster.com
SAN FRANCISCO · US
—
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from monster.com
We're looking for an Applied ML Engineer who thrives at the intersection of applied research and building real-world products, working directly with strategic customers to identify high-leverage opportunities and build production-grade ML solutions. You'll design adaptive ML systems across varied customer tech stacks, own outcomes from discovery through deployment, and raise the bar through compelling demos and technical presentations.
Responsibilities
- Find and Unlock Alpha: Go deep on customer problems and data workflows to identify the highest-leverage opportunities and build solutions.
- Ship What's Missing: Identify product gaps through hands-on customer engagement and implement production-grade ML solutions.
- Drive Adaptable Data Strategy: Lead design and implementation of efficient, adaptive ML systems across production environments and varied tech stacks.
- Own the Outcome: Serve as strategic and technical partner from discovery through deployment, accountable for results.
- Raise the Bar: Develop compelling demos, deliver technical presentations to senior stakeholders, and set the standard for customer excellence.
Requirements
- 4+ years experience in machine learning, applied research, or systems-level engineering for AI
- 2+ years in a customer-facing technical role
adaption
San Francisco · US · 5+ employees
Adapts focuses on agentic enterprise modernization, utilizing a deterministic code ontology engine to map and understand complex enterprise codebases for automated logic extraction and code generation.
