AI Engineer / MLOps Engineer

Stellenbeschreibung:

AI Engineer - Munich

Briefing Notes – The client is looking for Triple‑A candidates. Apart from the hard skills, the cultural fit is extremely important. Candidates must be able to:

Deal with a lack of structure in fast‑paced startup environments
Work 100% on an operational level and not be afraid to get their hands dirty
Build things on their own (0‑>1)
Have a strong ownership mentality
Go the extra mile on a regular basis (this isn’t a 9‑to‑5 job)

Company Overview

Name: VESTIGAS GmbH
Industry: Construction Tech / Supply‑Chain SaaS
HQ & Locations: Munich (Goetheplatz), Germany; operations also in Austria & other EU markets
Founded / Size: ~2019‑2020; ~50 employees (Jan 2026) with plans to grow to 75+ in 2026
Funding Stage: Post‑Seed (EUR 8 m Seed round closed early 2025; runway until mid‑2027)
Core Business: Digital, independent & legally secure platform for orders, delivery notes and invoices in B2B supply chains (starting with construction)
Mission & Vision: Fully digitise the construction industry’s supply‑chain documents, saving >€10 bn costs and several million tons of CO₂ in Germany alone
Key Values: Customer obsession, can‑do attitude, action bias, open & transparent communication, going the extra mile
Culture & Work Environment: Fast‑growing start‑up, flat hierarchies, high ownership, hybrid work model, team of ambitious problem‑solvers

Role Overview

Job Title: (Senior) AI Engineer / MLOps Engineer (m/f/d)
Department / Team: Engineering – AI / Machine Learning
Reason for Hiring: Growth & capability gap – need an experienced owner for MLOps and AI feature delivery
No. of Vacancies: 1

Location & Working Model

Primary Location: Munich, Germany (Goetheplatz office)
Remote / Hybrid / On‑Site Policy: Hybrid – 2‑3 days per week in office; no relocation offered (candidates must already be in Greater Munich area)

Key Responsibilities

Lead MLOps processes; build & maintain reliable, scalable, secure AI infrastructure on Azure
Align technical initiatives with customer needs; support sales & product to drive measurable client value
Design & implement advanced features for the AI‑driven supply‑chain operating system
Ensure smooth integration of ML models & data pipelines into production systems
Improve accuracy, efficiency & uncertainty estimation of existing AI features; conduct rigorous testing
Contribute to scalability, maintainability & core functionality of AI solutions and develop new ones
Establish and uphold high engineering standards, tooling and processes

Ideal Candidate Profile

5+ years hands‑on MLOps / ML engineering (end‑to‑end lifecycle)
Strong Python & Azure proficiency
Experience with NLP, image processing, generative AI & OCR
Bachelor’s or Master’s in Engineering or related field
German B2 (reading) & English C1 fluency
Leadership ambition while being 100 % hands‑on
Previous experience in a German company and ability to work hybrid in Munich

Nice‑to‑Haves

Terraform expertise
Technical or disciplinary leadership experience
Domain knowledge in construction / supply‑chain tech

Dealbreakers / Red Flags

No proven MLOps experience or <5 years relevant practice
Insufficient Python/Azure skills
Language level below German B2 or English C1
Requires relocation or cannot be on‑site 2‑3 days weekly
Purely research‑oriented mindset with low customer focus

Personality Traits

Customer‑obsessed, pragmatic, ownership mentality, proactive problem‑solver
Thrives in fast‑paced start‑ups; willing to go the extra mile
Strong communicator & collaborator

Education & Experience

5+ years ML engineering/MLOps, deploying & operating ML models at scale, generative AI, NLP, computer vision
Bachelor’s or Master’s in Engineering, Computer Science, Mathematics or related; PhD nice‑to‑have
Specific Tools/Technologies: Python, Azure (including AI services), ML frameworks (PyTorch, TensorFlow, etc.), Terraform (nice), MLOps tooling (e.g., MLflow, Kubeflow), OCR libraries