MLOps Engineer für Heidelberg gesucht
Arbeits- und Stellenangebot im Regiobizz Arbeitsmarkt
Job Kategorie: IT/IT-Dienstleistung Informationstechnologie (IT)
Stellenangebot Basisdaten
- Arbeitsort:
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DE 69118 Heidelberg
- Umkreis:
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keine Angabe.
- Art der Arbeitsstelle:
-
- Letze Aktualisierung:
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06.02.20262026-02-06
Stellenausschreibung: MLOps Engineer
- Arbeitgeber bzw.
Arbeitsvermittler
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Enzo in Hamburg
- Branche
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IT/IT-Dienstleistung
- Kategorie
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Informationstechnologie (IT)
- Stellenbeschreibung
- Transform the future of insurance through purpose-driven technology
Enzo is a B2B PropTech & WaterTech startup redefining how the property
insurance and real estate industries prevent water damage. With our
proprietary IoT & AI solution, one.drop , we enable insurers to
protect properties before damage occurs, turning reactive claims
management into proactive risk mitigation. At Enzo, AI models only
matter if they run reliably, efficiently, and at scale. As our MLOps
Engineer, you’ll own the bridge between model development and
real-world production, ensuring our AI systems can process millions of
sensor data points per day with high performance, reliability, and
observability. You’ll work closely with AI engineers, backend
engineers, and the founding team to professionalize our ML
infrastructure and deployment pipelines. This is a hands-on,
high-impact role with real ownership from day one. Tasks Role Overview
As MLOps Engineer, you are responsible for turning ML prototypes into
production-grade systems. Your mission is to design, build, and
operate a robust ML platform, from data ingestion to inference,
monitoring, and CI/CD, that scales with Enzo’s growth and supports
fast iteration. Level: Senior or Mid (5+ Years experience) Stack:
Python, TypeScript, GCP ** What You’ll Do** ML Infrastructure &
CI/CD Design and implement CI/CD pipelines for ML training and
inference. Build reproducible, versioned model deployment workflows.
Improve environment parity across dev, staging, and production.
Scalable Inference & Performance Design efficient inference pipelines
for time-series models processing millions of sensor data points per
day. Optimize latency, throughput, and cost across cloud
infrastructure. Implement rollout, rollback, and monitoring strategies
for ML services. Data Pipelines & Systems Integration Build and
maintain data pipelines in TypeScript for ingesting, validating, and
transforming IoT sensor data. Collaborate closely with AI engineers
working in Python, understand model code and algorithmic requirements.
Ensure clean interfaces between data, models, and applications.
Observability & Reliability Implement monitoring for model
performance, data quality, drift, and system health. Define failure
modes and recovery strategies for ML systems in production. Improve
reliability through automation, testing, and clear operational
standards. Cross-Functional Collaboration Work side-by-side with AI
engineers to make models production-ready. Challenge assumptions
around scalability, cost, and operational risk. Help establish best
practices for ML engineering across the team. Requirements Strong
Systems Builder Experience shipping systems into production.
Understanding of ML lifecycles, inference constraints. Engineering
Excellence Strong understanding of Python ML codebases and algorithms.
Programming skills in TypeScript are a bonus. Experience with cloud
infrastructure (AWS, GCP, or similar). Performance & Scalability
Mindset You think in terms of throughput, latency, cost, and
reliability. You’ve optimized systems handling large-scale,
high-frequency data. Startup Attitude Hands-on, pragmatic, and
execution-focused. Comfortable owning systems end-to-end. You move
fast, but you care about doing things right. Languages Fluent in
English Benefits Build the foundation for AI systems that prevent
real-world damage. Mission-driven innovation: Help insurers move from
paying for damage to preventing it Direct impact: Your work shapes how
an entire industry tackles one of its biggest cost drivers Autonomy &
ownership: Freedom to design, test, and evolve our AI models Culture
of builders: Work alongside a team that values integrity, curiosity,
and execution Flat hierarchies, honest and direct communication with
an open-minded startup culture Free brainfood: unlimited coffee,
snacks, drinks, fresh fruits and more Great career and personal
development opportunities - we want you to grow with us If you’re
ready to redefine what partnership means in the insurance industry -
and help insurers succeed with Enzo as their trusted innovation
partner - we’d love to hear from you.
- Qualifikation
- Arbeitskräfte
- Verdienst:
- n.a.
- Bewerbung an
- Enzo
Am Strandkai 1
De 20457 Hamburg
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