Access to the @Indeed MCP server. Act as my remote translator job-hunting researcher. Your goal is to surface remote localization roles that fit me but are hard to find on Indeed (buried under title variants, and postings that hide whether the seat is production translation, localization project management, or post-editing machine translation).
About me
- Language pairs: [e.g., ES>EN, PT>EN]
- Specialism: [e.g., legal, medical, technical / general marketing]
- CAT tools: [e.g., Trados, memoQ, OmegaT / none]
- Post-editing acceptable? [e.g., yes / pure translation only]
- Set up translation memories and term bases? [e.g., yes / no]
- Linguistic QA on other translators? [e.g., yes / no]
- Volume I handle: [e.g., 5-8k words/day]
- Industries: [e.g., SaaS, legal, medical devices]
- Work arrangement: [fully remote / remote US-only / remote global]
- Target location(s): [any / specific country]
- Employment type: [full-time / part-time / freelance]
- Salary expectation: [range + currency, or "flag if listed"]
- Languages: [e.g., English, Spanish, Portuguese]
- Dealbreakers: [e.g., no pure MT review, must be salaried]
Step 0: Check tools
List the Indeed MCP tools you have available and briefly say how you'll use each one. Use every relevant tool (job search, job detail, and any company-info tool if present). Don't guess job data; only report what the tools return.
Step 1: Fan out across localization title variants
Build a search plan of 15-25 queries covering every way employers label translation roles:
1. Location = "Remote" + "translator"
2. Location = "Remote" + "translation specialist"
3. Location = "Remote" + "localization specialist"
4. Location = "Remote" + "localization project manager"
5. Location = "Remote" + "language reviewer"
6. Location = "Remote" + "post-editor" (flag — see Step 2)
7. Location = "Remote" + "translator" + "legal"
8. Location = "Remote" + "translator" + "technical"
9. Location = "Remote" + "localization" + "Trados"
10. Location = "Remote" + "MT" + "linguist" (flag — see Step 2)
11. Location = "Remote" + "subtitling" or "transcreation" (flag — see Step 2)
12. Location = "Remote" + "localization" + "games"
13. Location = "Remote" + "translator" + "Spanish to English"
14. Location = "Remote" + "translator" + "part-time" or "freelance"
15. Location = "Remote" + "linguist"
Show me the plan first in a short table (query, angle, why), then run it.
Step 2: Deduplicate and filter by translation fit
Deduplicate results. For each unique job, call the job detail tool and check:
- Is it production translation, localization PM, or post-editing MT? Report the split.
- Which language pairs exactly, and do I have them?
- Which specialism does it need, and have I worked in it?
- Is it MT-heavy, and do I use CAT tools and translation memory?
- Is it salaried, freelance, or paid per word?
- Is it actually translation, or on-site interpreting?
Discard anything that fails. Keep 15-20 strong matches.
Step 3: Score and rank
Rank the surviving jobs by:
- Language pair match (my pairs > pivot through another language > unrelated)
- Specialism match (mine > general)
- Workflow match (CAT tools and TM > MT review > none)
- Employment match (salaried > freelance > per word)
Step 4: Deliver and schedule
Present the top matches in a table: Language pair | Title | Company or agency | Role type | Specialism | Tools | Pay model | Why it fits | Link.
Then save this exact search as a scheduled task that runs every morning and reports only new matches I haven't seen before.