Scout24
Tech / AI / Software
SeniorMLOps/LLMOpsEngineer(m/f/d)
“Senior MLOps / LLMOps Engineer (m/f/d) at Scout24. Skills: MLOps, LLMOps, ML, LLM, generative AI, Python, scalable system design, production-grade systems. Build and operate scalable ML and LLM-based systems in production, with a focus on self-hosted models, evaluation frameworks, and platform reliability. help shape Scout24’s AI platform by enabling teams to efficiently develop, deploy, and scale both traditional ML and generative AI solutions for multi-modal use cases”
Industry & Context.
work from abroad for 10 days per year, support with your visa process, Bring your dog to work
What They're Looking For.
Must Have
experience in MLOps (CI/CD, Docker, Kubernetes) and operating production-grade systems, Proficiency in Python, solid software engineering and scalable system design skills, Hands-on experience with LLMs and generative AI technologies (e.g. GPT, Gemini or Anthropic-like models), Expertise in prompt engineering, agent orchestration, context management, and output validation, Experience with LLM evaluation frameworks and deploying self-hosted LLMs, Familiarity with cloud platforms (e.g. AWS, GCP) as well as DevOps, testing, and observability practices, communication skills and ability to collaborate with cross-functional teams and stakeholders
Nice to Have
Kubernetes a plus
What You'll Do.
Build and operate scalable ML and LLM-based systems in production
with a focus on self-hosted models
evaluation frameworks
and platform reliability
help shape Scout24’s AI platform by enabling teams to efficiently develop
and scale both traditional ML and generative AI solutions for multi-modal use cases
ensure ML/LLM applications are robust
establish best practices for LLMOps
including gateway services
and lifecycle management
while leveraging AI-native workflows to drive faster development and higher engineering productivity
Design and maintain scalable ML/LLM infrastructure and pipelines
Productionize traditional ML and generative AI solutions with cross-functional product teams
Own the ML/LLMOps lifecycle: prompting
evaluation and optimization
Build and evolve an LLM Gateway service to standardize access
Develop evaluation frameworks to measure quality
and reliability of LLM outputs
Design and implement MCP-compatible services to enable standardized context exchange between LLMs
Integrate MCP into internal platforms to support tool use
and agent-based workflows across teams
Work with AWS and integrate self-hosted open-source AI models for scalable
and system performance
Contribute to project management
stakeholder communication and cross-team collaboration
How You'll Work.
Team & Collaboration
collaborate with cross-functional teams and stakeholders; stakeholder communication; cross-team collaboration
Communication Scope
communication skills; stakeholder communication
Process & Methodology
project management
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