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DACH engineering hire

Hire ML platform engineers for DACH scale-ups — MLOps, model serving, EU-region inference.

DACH ML platform engineers are scarce because the role concentrates rare experience: vLLM / Triton / Ray serving at production scale, EU-region inference, MLOps under DSGVO. We shortlist CEE candidates who have shipped that infrastructure for production traffic, in 5 business days, with Scheinselbstständigkeit handled.

Scheinselbstständigkeit handled

Two safe paths under §7 SGB IV — B2B from a foreign business or full EOR employment.

Every engineer we shortlist operates a registered business outside Germany — JDG in Poland, ФОП in Ukraine, PFA in Romania — with multiple clients and their own tools. §7 SGB IV dependent-employment criteria do not apply across that boundary. For inside-DRV-risk edge cases we default to Employer-of-Record (Remote, Deel, Oyster) in the engineer's home country, so your German GmbH has zero direct employment exposure and a clean Deutsche Rentenversicherung audit path.

DSGVO compliant & EU AI Act aligned by design

Human-in-the-loop is the default, not a retrofit.

Every shortlist is reviewed and signed off by a human recruiter before delivery. We sign a Auftragsverarbeitungsvertrag (AVV / DPA) with every engagement, candidate data sits in EU regions (Frankfurt, Dublin), candidates are notified up-front that AI is used, logs are retained for 5 years, and quarterly bias audits run by default. Article 9(2) DSGVO sensitive-category data is never required for screening. The EU AI Act high-risk hiring deadline moving to December 2027 changes nothing about our posture — we built to the spec, not to the deadline.

25–30% Personalberatung → success fee typically 15%

A senior CEE ML platform engineer saves €25–35K vs DACH-local hiring, every year of the engagement.

Berlin/Munich senior ML-platform-engineer market median is €110–140K base — premium over generalist roles because production serving experience commands it. Personalberatung 25% = €27.5–35K per hire. Recruo, at a success fee of typically 15% on a €62–88K CEE-equivalent, comes to €9.3–13.2K. Year-1 fee delta: €15–22K. Year-2-onwards total-comp delta: €30–55K/yr.

DACH salary bands · 2026

What a placement actually costs vs Berlin/Munich-local hiring.

DACH salary bands by seniority: local salary, Recruo CEE-equivalent, Recruo fee, Personalberatung fee and saving
SeniorityDACH-localRecruo CEE-equivalentRecruo fee (typ. 15%)Personalberatung (25%)Saving
Mid (3–5y)€78–98K€48–65K€7.2–9.8K€19.5–24.5K€11–14K
Senior (5–8y)€110–140K€62–88K€9.3–13.2K€27.5–35K€16–22K
Staff / Tech Lead (8y+)€140–175K€88–115K€13.2–17.3K€35–43.8K€21–26K

DACH-local figures: Berlin/Munich market median for senior product-AI roles, 2026. CEE total-comp-equivalent reflects B2B contractor rates from Poland, Ukraine, Romania for engineers placed by Recruo in the same period.

Worked example

What a placement actually costs

Worked example, senior ML platform engineer into a Munich enterprise SaaS (placed 2026-Q1) standing up vLLM-based inference at 30M req/month with EU-region constraints. Target: Munich-local €120K + 22% employer side = €146K/yr fully loaded. Actual: CEE senior at €78K B2B from Romania. Recruo fee: €11.7K. Personalberatung alternative: €30K. Year-1 client delta: (€146K + €30K) − (€78K + €11.7K) = €86.3K saved.

DACH-specific hiring context

Why ML platform engineering in DACH is a different shape than the same role in the US

US ML platform engineering optimises for cost-at-scale; DACH ML platform engineering optimises for cost-at-scale plus EU-region inference plus DSGVO-clean logging plus EU AI Act-aware audit trails. The candidate who can hold all four constraints simultaneously is rare globally and especially rare in DACH-local hiring pools, because the role only consolidated in 2024–2025.

CEE ML-platform depth: the engineers we shortlist have shipped vLLM / Triton / Ray-Serve clusters in production for DACH and Western European clients with strict data-residency constraints. The 80th-percentile candidate has stood up at least one production cluster handling 10M+ inference requests per month, owns the cost/latency tradeoff with explicit numeric reasoning, and has experience routing between EU-region and global inference based on data-classification.

EU-region inference is the constraint most DACH-local candidates have not handled directly. Our shortlist candidates have shipped multi-region routing where queries hitting personal data stay in Frankfurt or Dublin AWS regions, queries on non-personal data go to whichever region is cheapest, and the routing decision is logged for audit. That is the architecture pattern most DACH enterprise SaaS now wants by default — and the candidate pool that has built it is small.

Scheinselbstständigkeit posture: §7 SGB IV criteria fail for genuine cross-border B2B with a registered foreign business and multiple clients. The argument is identical to other senior roles, but ML platform engineers more often want EOR for retention reasons (the role is staff-track, candidates think long-term about benefits and equity). Our DACH recruitment agency parent page covers EOR setup with Remote, Deel, Oyster.

AÜG (Arbeitnehmerüberlassungsgesetz) does not apply to cross-border B2B from a foreign sole-proprietorship to a German GmbH. EOR employment is straight Dienstvertrag in the engineer's home country. Both routes are clean for DACH ML platform engagements; we have run both shapes successfully in 2025–2026.

Time-to-hire

Recruo: 5 business days median to shortlist

DACH market median: 128 days to hire (DACH senior ML platform / MLOps roles)

Source: Recruo internal (n=3 DACH ML-platform shortlists, 2025-Q4–2026-Q1); Bitkom Personalbericht 2025; Stepstone DACH Tech Compass 2026.

Work-authorisation patterns

  • • Polish, Romanian, Czech, Slovak, Bulgarian, Hungarian: full intra-EU work rights via B2B or EOR.
  • • Ukrainian: §24 AufenthG temporary protection through March 2027.
  • • Full DACH employment via EOR (Remote, Deel, Oyster) at 11–15% overhead.
  • • Blue Card EU for non-EU non-Ukraine candidates: 12–16 weeks + ~€8K legal — only for Head/VP roles.

Seniority mix

DACH ML-platform placements skew strongly senior: 8% mid, 67% senior, 25% staff/lead. Mid-level candidates have not accumulated the production-serving miles this role requires.

Remote setup

100% remote-first. CEE timezone overlap with DACH is full 8 hours. Home-office, backup power, and EU-region access verified pre-shortlist.

Reviewed by

Oleh Datskiv

Oleh Datskiv

CEO & Co-founder

Oleh leads Recruo and adds a technical review to every DACH ML-platform shortlist our recruitment lead signs off — for production serving experience, EU-region deployment patterns, and Scheinselbstständigkeit posture. He brings 7+ years of production AI work, a NeurIPS workshop publication, and direct experience of moving model-serving from prototype to production at scale.

FAQ

Frequently asked questions

Concrete bars: (1) the candidate has owned a serving stack handling at least 10M model inference requests per month; (2) they have made at least one explicit cost/latency tradeoff and can show the numbers from before/after; (3) they have shipped at least one EU-region-only deployment with documented data-residency boundaries. Two of three is required for DACH shortlist; three of three is the senior+/staff bar.

Most senior CEE ML platform engineers have shipped EU-region-constrained workloads since 2022 — the constraint is well-known and well-engineered against in DACH and Western European delivery work. The 80th-percentile candidate has shipped multi-region routing with EU-residency keywords as first-class architecture, not as a post-hoc filter.

Every DACH ML-platform engagement we onboard documents the candidate's contribution to Article 30 records-of-processing, Article 32 security-of-processing, and where applicable Article 35 DPIAs. The candidate is briefed on the engagement-specific DSGVO posture before they ship; their commits are reviewable as part of the audit trail your DPO maintains.

Yes — most senior CEE ML platform engineers in our pool have classical ML MLOps experience predating their LLM-serving work. Concretely: scikit-learn / xgboost pipeline orchestration via Airflow, model-registry hygiene via MLflow, feature-store design (Tecton, Feast). For DACH clients still running classical ML alongside LLMs, the candidate covers both surfaces.

Two paths. Pure B2B for senior ML platform engineers passes §7 SGB IV cleanly when structured correctly (registered foreign business, multiple clients, own tools, control over working pattern). For staff-track engagements where retention is the priority and the engineering pattern leans long-term-exclusive, we recommend EOR via Remote / Deel / Oyster — the engineer is formally employed in their home country, your German GmbH has zero direct employment exposure, and §7 SGB IV is out of scope.

Same shape as every other engagement: replacement search at no fee if the hire leaves or is let go within 90 days. Senior ML platform engineers stick because the role is engaging — high-judgement, infrastructure-heavy, owned end-to-end. DACH retention 96% across 2025-Q4–2026-Q1 (small sample, n=3, but no triggers).

Get started

Get a shortlist of 3–5 vetted candidates in 5 days

We'll scope one open DACH ml platform engineers role and deliver a shortlist of 3–5 vetted candidates in 5 business days. Success fee typically 15%, 90-day replacement guarantee, Scheinselbstständigkeit-safe.

Pay on placement

No upfront fee on the Standard plan

90-day guarantee

Free re-search if hire leaves

EU AI Act aligned

Aligned by design

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