# Jobgether (client undisclosed) — AI Researcher

| Field | Value |
|---|---|
| **Date found** | 2026-06-14 |
| **Company** | Jobgether (client undisclosed) |
| **Role** | AI Researcher |
| **Location** | Ireland — Fully Remote (global) |
| **Salary** | Undisclosed |
| **Job URL** | [LinkedIn](https://www.linkedin.com/jobs/view/4426972476/) |
| **Status** | New |

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## Company Research

Recruiting agency — client undisclosed.

Jobgether is an AI-powered job matching platform that lists roles on behalf of partner companies. The hiring client is a "global AI research organization" building agentic and multimodal AI systems trained on real-world interaction data. No further public details available.

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## Job Summary

**What they do:** Unknown client (via Jobgether) — a global AI research organization focused on agentic AI systems trained on real-world interaction and multimodal data (text, audio, logs, structured workflows).

**The role:** AI Researcher at the frontier of agentic AI research — designing and experimenting with learning frameworks to improve reasoning, planning, and tool use in production AI agents.

**Core work:**
- Research agentic AI systems trained on real-world interaction data (RLHF, DPO, GRPO, RAG, fine-tuning)
- Develop multimodal representation learning approaches (joint embedding spaces across text, audio, logs)
- Improve speech and audio intelligence systems (STT, ASR, audio-driven learning pipelines)
- Define evaluation methodologies for agent performance in real-world environments
- Translate behavioral signals into structured training objectives; collaborate with engineering to bring research to production

**Stack:** Python · PyTorch · HuggingFace Transformers · RLHF · DPO · GRPO · RAG · LLM fine-tuning · multimodal embeddings · speech/audio modeling (STT/ASR)

**Work style:** Fully remote, globally. High IC autonomy. Research-to-production mandate.

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## Score: 77%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 80% | Frontier agentic AI research — RLHF/DPO/GRPO for agentic post-training, evaluation frameworks, reasoning and planning improvement. Very deep but on the research/training side rather than deployed agentic systems. |
| Tech fit (25%) | 60% | Python/PyTorch/HuggingFace match well; RLHF/fine-tuning overlap is solid. However, speech/audio modeling (STT, ASR, multimodal embeddings) are weaker areas. ⚠️ PhD required — major practical gap. |
| Remote fit (25%) | 100% | Fully remote, globally. No on-site requirement stated. |
| Company culture fit (15%) | 55% | "Global AI research organization" — likely a product company with a research team. Unknown client via Jobgether adds significant uncertainty about culture, team size, and work environment. |
| IC/leadership balance (10%) | 90% | Strong IC research ownership — "strong ownership over research direction and technical strategy". No management. |
| **Final (weighted)** | **77%** | Excellent remote fit and deep agentic AI scope. PhD requirement is a major practical blocker for application. |

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## Strengths

- Deep agentic AI research scope: RLHF, DPO, GRPO, agentic post-training — frontier work
- Fully remote globally with strong IC ownership
- Direct production deployment mandate — research translates into shipped systems
- PyTorch/HuggingFace/fine-tuning overlap with Luca's ML background

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## Weaknesses & Risks

- ⚠️ PhD in CS/ML/AI explicitly required — major qualification gap
- Client is anonymous (via Jobgether) — culture, team, and company stage entirely unknown
- Speech/audio modeling (STT, ASR) is a weaker area of fit
- ⚠️ Potential duplicate of #074 (Expired) — another Jobgether AI research role with similar scope
- Salary undisclosed; "competitive compensation aligned with experience" gives no floor

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## Suggestions

- Consider applying only if comfortable being candid about PhD gap and strong on RLHF/DPO work
- Ask Jobgether to disclose the client company before investing time in the process
- Highlight any RLHF, fine-tuning, or post-training work from Fenergo/past projects

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## Interview Tracker

| Stage | Date | Notes |
|---|---|---|
| Applied | | |
| Recruiter screen | | |
| Technical interview | | |
| Final round | | |
| Offer / Outcome | | |