AI Engineer / MLOps Engineer

Trades Workforce Solutions; Deutschland; Hybrid; EUR 80.000 - 100.000; Vollzeit

Zusammenfassung

A leading tech company in Munich seeks a Senior AI Engineer to focus on MLOps and AI feature delivery within a hybrid model. Candidates should have over 5 years of experience, strong skills in Python and Azure, and a passion for embedded AI solutions. This position emphasizes substantial technical challenges in a fast-paced startup environment, and offers competitive compensation and an equity participation plan. Join a team that values ownership and innovation.

Leistungen

VSOP equity participation

Subsidised gym membership

Subsidised Deutschlandticket

Flexible working hours

Flat hierarchies

Team events

Qualifikationen

• 5+ years hands-on MLOps / ML engineering experience.
• Strong Python & Azure proficiency.
• Experience with NLP, image processing, generative AI, and OCR.

Aufgaben

• Lead MLOps processes; build & maintain AI infrastructure on Azure.
• Align technical initiatives with customer needs.
• Design & implement advanced features for the AI-driven supply-chain system.

Kenntnisse

MLOps

Python

Azure

NLP

Generative AI

Collaboration

Ausbildung

Bachelor's or Master's in Engineering, Computer Science, Mathematics or related

Tools

Terraform

PyTorch

TensorFlow

MLflow

Kubeflow

Jobbeschreibung

AI Engineer - Munich

Briefing Notes - Extra Recruiting Requirement - Please note: The client is looking for Triple A candidates. Apart from the hard skills the cultural fit is extremely important. We are looking for candidates who:

• can deal with a lack of structure in fast paced startup environments
• are ready to work 100% on an operational level and who are not afraid to get their hands dirty
• are willing and able to build things on their own (0 --> 1)
• have a strong ownership mentality
• are willing to go the extra mile on a regular basis (this ain't no 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
• Unique Selling Points: Market-leading traction (14/20 top German construction companies onboard), greenfield AI challenges, strong funding, equity participation, direct industry impact

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 Must-Haves

• 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

Experience & Education

• Experience: 5+ years ML engineering/MLOps, deploying & operating ML models at scale, generative AI, NLP, computer vision
• Education: 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

Compensation

• Base Salary Range: €80,000 – €100,000 gross p.a.
• Variable/Bonus: VSOP (employee share options) >= optional

Contract Details

• Contract Type: Permanent (unbefristet)
• Working Hours: 40 h/week (full‑time)
• Vacation Days: 26 (negotiable to 28)
• Probation Period: 6 months

Perks

• VSOP equity participation
• Wellpass subsidised gym membership
• Subsidised Deutschlandticket
• Flexible working hours & hybrid model
• Flat hierarchies & high responsibility
• Construction site visits & cool team events