# Immersum (client undisclosed) — Principal Machine Learning Engineer

| Field | Value |
|---|---|
| **Date found** | 2026-05-21 |
| **Company** | Immersum (client: undisclosed AI consultancy) |
| **Role** | Principal Machine Learning Engineer |
| **Location** | Dublin, Hybrid (remote-first, client site presence) |
| **Salary** | €120k–€200k EUR |
| **Job URL** | [LinkedIn](https://www.linkedin.com/jobs/view/4407869603/) |
| **Status** | New |

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## Company Research

Recruiting agency (Immersum) — end client undisclosed.

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## Job Summary

**What they do:** Client is an unnamed fast-growing AI consultancy delivering ML systems into regulated industries (pharma, biopharma, medtech, manufacturing).

**The role:** Principal ML Engineer — client-facing, end-to-end ownership from problem definition to prototype to production.

**Core work:**
- Deliver classical ML and statistical modelling solutions in regulated environments
- Communicate directly with client stakeholders at every stage
- Growing exposure to LLMs as an emerging area of work

**Stack:** Python · AWS/Azure · classical ML · statistical modelling · LLMs (peripheral)

**Work style:** Remote-first; client site presence required (frequency unspecified — likely significant)

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## Score: 47%

| Dimension | Score | Justification |
|---|---|---|
| Agentic AI depth (25%) | 25% | Generic applied ML consultancy role. LLMs described as "increasing exposure" — explicitly not the focus. No mention of agentic AI, multi-agent systems, or LLM orchestration |
| Tech fit (25%) | 50% | Python ✅, AWS/Azure ✅, LLMs (peripheral) ✅. Missing: PyTorch, LangChain/LangGraph/CrewAI, Anthropic APIs. Classical ML and stats-heavy stack |
| Remote fit (25%) | 45% | "Remote-first" is positive but this is a client-facing consulting role — client site visit frequency not stated and likely significant. Needs clarification before applying |
| Company culture fit (15%) | 55% | "Fast-growing AI consultancy" signals are reasonable but the actual employer is fully anonymous. Regulated environments (pharma, GxP, ISO) suggest process-heavy culture |
| IC/leadership balance (10%) | 85% | End-to-end ownership with no management responsibilities. Client-facing communication required but not people management |
| **Final (weighted)** | **47%** | |

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## Strengths

- Salary explicitly stated: €120k–€200k — well above the €110k floor, strong compensation signal
- Principal-level IC with full end-to-end ownership (idea → prototype → production)
- Remote-first framing — positive baseline, even if client visits are expected
- "Fast-growing AI consultancy" with interesting regulated-domain problems
- Fenergo experience (regulated environments, compliance data) is a direct match for pharma/biopharma framing
- Applied, delivery-focused culture — "pragmatic, care more about impact than elegance"

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## Weaknesses & Risks

- **No agentic AI focus** — this is classical ML + stats + LLMs as an add-on. Not aligned with the agentic AI career direction
- **Client anonymous** — actual employer unknown; culture, stability, and working conditions unclear before first contact
- **Client site visits** — frequency unspecified. For a consulting firm this could easily be multiple days per week, which would fail the location hard filter
- **Recruiting agency posting** — adds a layer of indirection; Immersum is the intermediary, not the employer
- **Classical ML/stats bias** — strong fundamentals requirement is fine, but the role is not pushing into advanced agentic AI territory
- **Regulated industry focus** (pharma/biopharma/medtech) — niche domain Luca has no direct experience in

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## Suggestions

- Clarify client site visit frequency before investing time — if it's more than 1–2 days/month the location filter fails
- Ask who the actual employer is early in the process; anonymous client is a meaningful risk
- If pursuing, lead with the Fenergo regulated-environment experience (KYC compliance = regulated domain = production ML in complex environments)
- The €120k–€200k range is notable — if the upper end is realistic this is financially interesting even if agentic AI depth is low
- Not a good fit for the agentic AI career direction, but a strong financial safety net option if other roles stall

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## Interview Tracker

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