Senior Python Engineer (MLAI Services)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
TL;DR
Senior Python Engineer (MLAI Services): Building AI-powered services and APIs, leveraging LLMs and custom ML models, with an accent on intelligent automation, agentic workflows, and large-scale retrieval services. Focus on transforming advanced AI concepts into reliable, scalable, and secure solutions used across our enterprise ecosystem.
Location: Berlin, Frankfurt, Munich, Germany
Company
helps businesses globally streamline operations by connecting data, processes, applications, and experiences.
What you will do
- Design, build, and maintain AI-powered services and APIs, leveraging LLMs and custom ML models.
- Develop an enterprise-grade agentic framework that enables orchestration, retrieval, and collaboration between multiple AI agents.
- Implement and optimize knowledge retrieval systems and agentic search capabilities using vector databases such as Qdrant and ElasticSearch.
- Write well-structured, efficient, and testable Python code for production services, experimentation, and internal developer tools.
- Collaborate with cross-functional teams on architecture, internal protocols, and API standards to ensure consistency and reliability across the platform.
- Drive the full software development lifecycle - from design and implementation to deployment, monitoring, and continuous improvement.
Requirements
- Bachelorβs or Masterβs degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 5+ years of experience as a Software Engineer, with strong proficiency in Python.
- Proven track record of building and maintaining production-grade systems using Python.
- Strong understanding of distributed systems, API design, and data-driven architectures.
- Experience with relational and non-relational databases (PostgreSQL, Elastic, Qdrant, or similar).
- Familiarity with AI/ML system design, including LLM integration and evaluation pipelines.
Nice to have
- Experience working with multiple LLM providers (OpenAI, Anthropic, Qwen, open-source models).
- Background in developer platforms or AI infrastructure services.
- Familiarity with vector databases, semantic retrieval, and knowledge graph architectures.
Culture & Benefits
- Fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles.
- Driven by innovation and looking for team players who want to actively build our company.
- Balancing productivity with self-care.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β