AI/ML Engineer
Tasks
- Build and enhance retrieval-augmented generation systems
- Create text to SQL capabilities
- Design and deploy predictive machine learning models
- Develop recommendation systems
- Ensure robust data pipelines and datasets
- Integrate LLMs with vector databases
- Monitor and improve production model performance
- Research and apply algorithms to improve accuracy and scalability
Perks/Benefits
- English courses
- Health and wellness programs
- Meetups
- Offline Internal Events
- Pet-friendly office
- Professional training
- Udemy for business
- Volunteering support
Skills/Tech-stack
AWS | AWS Bedrock | Agile | Azure | CI/CD | Cloud platform | CloudFormation | Collaborative Filtering | Content-Based Filtering | Content-based | Decision Trees | Docker | Google Cloud | Google Cloud Platform | Gradient boosting | Kubeflow | Kubernetes | Langchain | Langgraph | Llamaindex | MLOps | MLflow | Machine Learning | NumPy | Pandas | Pinecone | PyTorch | Pydantic | Python | Random Forest | Recommendation Systems | Retrieval-Augmented Generation | SQL | Scikit-learn | TensorFlow | Text-to-SQL | Vector Databases | Weaviate | XGBoost
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer
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