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Senior Data Scientist/ML Engineer/AI Engineer (f/m/x)

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KI-Zusammenfassung

In dieser Position sind Sie verantwortlich für die End-to-End-Entwicklung von ML- und AI-Anwendungen, einschließlich der Gestaltung von Agentenarchitekturen und der Implementierung von Standards für die Tool-Integration. Sie arbeiten eng mit Produktverantwortlichen und Ingenieuren zusammen, um skalierbare Lösungen zu entwickeln und zu optimieren. Zudem fördern Sie die Zuverlässigkeit und Sicherheit der Systeme und dokumentieren Ihre Arbeit klar.

apsa personnel concepts gmbh

Senior Data Scientist/ML Engineer/AI Engineer (f/m/x)

  • Wien
  • Vollzeit
  • ab €

 

Industry: Artificial Intelligence & ML

Location: Vienna Hybrid

Capacity: Full-time

Duration: Long-term

Language: English

 

These are your responsibilities:

  • End-to-end responsibility for ML, AI, and agent-based AI use cases: from problem definition to data preparation, modeling, orchestration, evaluation, and production deployment.
  • Design of agent architectures (e.g., planner–executor, multi-agent collaboration) with features like memory, reflection, and tool use, taking into account robustness, transparency, and controllability.
  • Implementation of the Model Context Protocol (MCP) for standardized and secure tool integration as well as capability detection across internal and external services.
  • Orchestration of LLMs and tools using agent frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, OpenAI Assistants), including function/tool calls, fallbacks, and guardrails.
  • Development and optimization of RAG pipelines (Retrieval-Augmented Generation): data ingestion, chunking, embedding, vector storage, retrieval strategies, caching, and evaluation in terms of precision, recall, and latency.
  • Establishment of robust LLMOps/MLOps practices: experiment tracking, prompt and data versioning, CI/CD, model and artifact management, monitoring, and incident response.
  • Promotion of reliability, security, and compliance: protection against prompt injection, content filtering, policy enforcement, red-teaming, and measurable quality controls.
  • Conducting rigorous offline/online evaluations: backtesting, time series cross-validation, A/B and shadow deployments, canary releases, drift and impact monitoring.
  • Optimization of performance and cost: latency, throughput, rate limits, batching, streaming, caching, and development of monitoring dashboards for usage and cost.
  • Close collaboration with product owners, engineers, and business stakeholders; implementation of scalable solutions on Databricks (AWS) and integration into banking systems.
  • Creation of clear documentation, templates, and playbooks; mentoring of colleagues and contribution to best practices in the community.

You bring:

  • 3+ years of professional experience in developing and operating software solutions.
  • You are a team player, enjoy collaborative work, but are also capable of solving problems independently.
  • 2+ years of hands-on experience with cloud computing on AWS, especially with AWS Linux and AWS Lambda.
  • 2+ years of experience working with various database technologies and ideally with data lakes (e.g., AWS S3).
  • 2+ years of experience in a product-driven environment.
  • Programming skills in Python (ideally with Django) and experience in building RESTful APIs.
  • Proven experience in setting up processes for data transformation, data structuring, metadata management, and workload management.
  • Basic knowledge of ETL tools.
  • Familiarity with agile working methods.

Soft skills:

  • Initiative, curiosity, sense of responsibility as well as creative ideas & self-confidence.
  • Structured approach to work and strong problem-solving skills.
  • Fluent English spoken and written; German or another CEE language is a plus, but not required.

 

JobNr: 3379 

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