AI Engineer
Tasks
- Apply deep learning and NLP to business problems
- Build integrate RAG systems and vector search
- Collaborate on data pipelines and domain datasets
- Containerize and deploy with Kubernetes
- Deploy AI systems on Azure or GCP
- Design scalable LLM and ML architectures
- Design test and optimize LLM prompts
- Develop LLM and RAG solutions
- Implement clean code and engineering best practices
- Implement responsible AI solutions
- Participate in full AI product lifecycle
- Perform data exploration preparation and modeling
Perks/Benefits
- Certification support
- E-learning platform
- Hybrid work
- Life insurance
- Lunch subsidy
- Medical insurance
- Online training
- Social events
- Sport benefits
- Wellbeing platform
- Work from anywhere
Skills/Tech-stack
API Design | Agentic Architectures | Azure | Azure DevOps | BDD | CI/CD | Cloud Build | Concurrency | Deep learning | FastAPI | GCP | Google Cloud | Google Cloud Build | Jenkins | Kubernetes | LLM | Langchain | Machine Learning | Microservices | Monitoring | NLP | Observability | Prompt engineering | Python | RAG | Spring | TDD
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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