Senior AI Engineer
Tasks
- Advise stakeholders on AI capabilities and best practices
- Build and optimize data pipelines for AI/ML workflows
- Deploy and monitor production AI systems in cloud
- Design build and deploy LLM solutions
- Develop RAG evaluation and retrieval pipelines
- Develop optimize retrieval augmented generation applications
- Evaluate and iterate on AI system performance
- Implement MLOps monitoring and experiment tracking
- Integrate AI capabilities into products and internal tools
- Own end to end AI lifecycle
Perks/Benefits
- Asynchronous Working Environment
- Autonomy and flexibility
- Career development opportunities
- Hardware provided
- International Diverse Collaborative Environment
- Remote first working model
- Work abroad short periods
Skills/Tech-stack
AWS | Algorithm Design | Async Programming | Azure | CI/CD | Data Pipelines | Data Wrangling | Deep learning | Distributed Systems | Elasticsearch | Experiment tracking | FastAPI | Fine Tuning | Generative AI | Google Cloud | Language Models | Large Language Models | ML CI/CD | MLOps | Machine Learning | Monitoring | OpenSearch | Pinecone | Prompt engineering | Python | Qdrant | RAG evaluation | Retrieval-Augmented Generation | Semantic Search | Statistics | Vector Databases | Weaviate
Education
N/A
Roles
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