Machine Learning Reply
3 days ago
GenAI Engineer (m/f/d)
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Company information
- Company
- Machine Learning Reply
- Location
- Munich, Bayern, Germany Germany
- Posted
- 3 days ago
Job description
Tasks
As a GenAI Engineer (m/f/d), you will independently develop and implement Generative AI models, (multi-)agent-based LLM applications, and AI-based solutions for our customer-specific requirements. You will identify and analyze problems in the context of AI and generative models.
You will develop and maintain AI pipelines, APIs, and interactive applications and work on components such as Large Language Models, multimodal models, Knowledge Graphs, and AI-powered products.
Working on complex AI projects, analyzing business applications for generative AI, and translating them into technical solutions will complement your activities.
You will use your communication skills to work closely with our clients, analyze their problems in the context of GenAI, and present the results understandably.
You will work across various technology stacks, e.g., Azure, AWS, GCP, Databricks, LangChain, Hugging Face, OpenAI APIs, LLM frameworks, and cloud infrastructure.
You will mentor junior colleagues in the field of AI and ensure knowledge transfer within the team.
You will benefit from our team, learning resources, hackathons, and other opportunities to advance your technical development in Generative AI and be present in the community.
Benefits
Regular and systematic (external and internal) further training opportunities in Generative AI, LLM development, and cloud architecture
Access to cross-industry projects, e.g., banking, insurance, automotive, retail
Collaborations with leading partners in cloud, AI/ML, and AutoML and access to enterprise versions of leading LLMs
Work in an open, flat environment within a broad Reply network for knowledge exchange
Award-winning office spaces in the heart of Munich with access to the main train line
Deutschlandticket (Germany Ticket)
Support for sporting activities through EGYM Wellpass and other benefits from the Reply Group
Flexible working environment between client projects, Reply office, and remote work
Completed degree with a technical background, e.g., Computer Science, Business Informatics, (Business) Mathematics, Data Science, or similar
Experience with Generative AI, LLMs, NLP, and AI-based production systems; knowledge of Python, R, Rust, PySpark, or SQL
Experience in Context Engineering, Prompt Engineering, Fine-Tuning, Retrieval-Augmented Generation (RAG), or similar LLM techniques
Familiarity with cloud platforms such as AWS, GCP, or Azure, containerization, and deployment of AI models
Good communication skills in German and English
Willingness to learn, team player, and the ability to explain complex technical concepts understandably
Good project management skills and the ability to work both independently and in a team
About Machine Learning Reply
Machine Learning Reply offers customized end-to-end solutions in the data science field, covering the entire project lifecycle – from initial strategy consulting, data architecture, and infrastructure topics to data processing and quality assurance using machine learning algorithms. Machine Learning Reply possesses comprehensive expertise in data science across all key industries of German HDAX companies. Machine Learning Reply empowers its clients to successfully implement new data-driven business models and optimize existing processes and products – with a focus on open-source and cloud technologies. With the Machine Learning Incubator, the company offers a program for training the next generation of decision-makers, data scientists, and developers.
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Required skills
- databricks
- generative ai
- sql
- ai
- python
- aws
- nlp
- llm
- prompt engineering
- cloud technologies
- gcp
- azure
- apis
- machine learning
- genai
- data science
- rust
- large language models
- cloud platforms
- cloud infrastructure
- pyspark
- data architecture
- containerization
- data processing
- rag
- deployment
- r
- multi-agent systems
- langchain
- openai apis
- llm frameworks
- hugging face
- open-source
- fine-tuning
- multimodal models
- retrieval-augmented generation
- ai-based solutions
- knowledge graphs
- context engineering
- ai pipelines
- interactive applications
- ai-based production systems
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