AI Engineering I - Marketing
Tasks
- Build AI driven features and intelligent automation
- Build backend APIs data layers and frontend interfaces
- Design and develop AI powered platforms and systems
- Embed AI capabilities into workflows and products
- Implement systems for reliability performance and security
- Integrate AI into customer facing products and internal tools
- Own end-to-end delivery of AI projects
- Participate in code reviews and knowledge sharing
- Provide production support and incident response
- Translate business problems into AI enabled technical solutions
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agentic Systems | Attention Mechanisms | CI/CD | Distributed Systems | Docker | Embeddings | Entity recognition | Feature Engineering | Fine Tuning | GitLab | Graph Workflow Engine | Kubernetes | Langchain | Language Processing | Machine Learning | Make | Microservices | Model Evaluation | N8n | NLP | Named Entity Recognition | Natural Language | Natural Language Processing | PGVector | Pinecone | Python | React | SQL | Semantic Search | Similarity Search | Supervised Learning | Text Classification | Tokenization | Transformer Architectures | Unsupervised Learning | Vector Databases | Vector similarity | Vector similarity search | Weaviate | Workflow Engine
Education
N/A
Roles
Regions
Countries
States
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