SEARCH SYSTEMS ENGINEER - FULLY REMOTE | UPTO $150/HR
mercor
Part-timemid€80-150/hour
Job description
About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .
Position: Software Engineer — Agentic Search Systems
Type: Contract
Compensation: $80–$150/hour
Location: Remote
Role Responsibilities
• Evaluate the accuracy and depth of AI-generated content in search systems to strengthen reasoning and rigor in model outputs .
• Develop and optimize systems related to agentic search for improved performance and reliability.
• Scale data infrastructure to support modern search systems and enhance retrieval capabilities.
• Collaborate with AI research teams to quantify impact and improvements in search systems.
• Work independently and asynchronously to meet deadlines while improving AI model performance .
Qualifications
Must-Have
• Experience shipping production search systems.
• Ownership of relevance or retrieval on systems used by real users.
• Ability to quantify impact and improvements in search systems.
• Experience building systems related to agentic search .
• Experience scaling data infrastructure for search systems.
Interview Process
• 25 mins conversational interview. No coding, no take-home.
• Follow-up with a paid 30-minute live conversation if interview stands out; $200 for your time.
Application Process (Takes 20–30 mins to complete)
• Upload resume
• AI interview based on your resume
• Submit form
Resources & Support
• For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
• For any help or support, reach out to: support@mercor.com
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Skills
AI-generated contentagentic searchdata infrastructuresearch systemsrelevanceretrievalmodel performancesystem optimization