1. Indexing technical proof
Candidate profiles: declared stack, GitHub repos, papers, contributions, Ganloss test results (LLM, RAG, MLOps).
Recruiters filter by skills and review deliverables before outreach — not after three interviews.
Shipped work beats CV keywords — how Ganloss qualifies mid and senior AI profiles.
Recruiter guide · matching on shipped projects

Remote Discord LLM engineer for community copilots and summarization — product GenAI with strong safety bars.

Remote US Groq ML systems role — runtime, scheduling, and developer APIs for high-throughput LLM inference.

Groq LLM inference engineer jobs — ultra-low-latency serving on LPUs, compiler tooling, and API performance in Mountain View.

ServiceNow MLOps engineer for model CI/CD and GPU serving — Bellevue / Seattle hybrid enterprise AI platform.

ServiceNow AI jobs: LLM engineer on Now Assist for IT and HR workflows — enterprise RAG, guardrails, and evals in Santa Clara.

Dropbox LLM engineer for AI writing and file copilots — Seattle hybrid with TypeScript + Python stack.

Dropbox Dash RAG engineer — enterprise knowledge retrieval, citations, and permission-aware search in San Francisco.

Remote US Pinterest GenAI role for generative Pin experiences — diffusion, evals, and creator-facing APIs.

Pinterest ML engineer jobs on visual search and embedding retrieval — computer vision for Pins in San Francisco.

DoorDash GenAI for merchant menus, support, and ops copilots — Seattle hybrid LLM engineering.

LinkedIn AI jobs: LLM engineer on Job Matching and Recruiter copilots — retrieval, ranking, and fairness evals in Sunnyvale.

Uber GenAI engineer building rider and driver support agents with RAG, tool use, and eval harnesses — Seattle hybrid.
Candidate profiles: declared stack, GitHub repos, papers, contributions, Ganloss test results (LLM, RAG, MLOps).
Recruiters filter by skills and review deliverables before outreach — not after three interviews.
Structured JobPosting listings, salary shown, explicit stack — typically indexed within 24 hours.
Active candidates get recommendations based on their projects and your job description.