Remote ML Engineer II: Vector Search & Production Systems

Ladders; United States; Remote; USD 129,000 - 170,000; Full time

Benefits offered by this job

Generous time off and wellness leave

Comprehensive healthcare coverage

Retirement savings program

Opportunities for equity participation

Job summary

Ladders is seeking a Machine Learning Engineer 2 for a remote role focused on building and improving ML systems that convert raw data into reliable customer insights. You will work with data, retrieval, and evaluation layers to speed access to information and improve production performance.

Partner with Product and ML teams to translate customer needs into scalable technical improvements, while contributing to memory quality benchmarks and robust observability practices.

Qualifications

• 5-7 years of experience building backend services with adaptability to new languages and frameworks.
• Curiosity in service management and a commitment to understanding system behavior in production.
• Experience or willingness to learn about evaluation and quality measurement systems.
• Strong knowledge of observability practices, including structured logging and metrics for debugging.
• Proficiency with AI-assisted development tools, applying them thoughtfully.

Responsibilities

• Build extraction pipelines that convert raw data into structured customer memory.
• Own the retrieval path for quick access to customer information using embeddings and vector search.
• Contribute to evaluation systems that measure memory quality and establish benchmarks.
• Diagnose production issues across data ingestion, extraction, and indexing paths.
• Collaborate with Product and ML teams to translate customer needs into system improvements.

Skills

Backend development

Observability

AI-assisted development tools

Embeddings and vector search

Tools

Embeddings

Vector search

Structured logging

Metrics for debugging

Job description

Ladders is seeking a Machine Learning Engineer 2 for a remote role focused on building and improving ML systems that convert raw data into reliable customer insights. You will work with data, retrieval, and evaluation layers to speed access to information and improve production performance.

Partner with Product and ML teams to translate customer needs into scalable technical improvements, while contributing to memory quality benchmarks and robust observability practices.