Software Engineer AI/ML
Tasks
- Build REST APIs for model serving
- Build vector database and semantic search
- Create MLOps experiment tracking pipelines
- Create documentation and reference architectures
- Deploy models on AWS
- Design data pipelines for feature engineering
- Develop AI/ML products
- Develop LLM-powered applications
- Ensure responsible AI with bias detection
- Establish automated model evaluation
- Evaluate model performance
- Implement RAG systems
- Implement model explainability
- Perform A B testing for models
- Set up monitoring and logging
- Train machine learning models
- Translate requirements into AI ML roadmap
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | API Authentication | AWS | Anomaly Detection | Artificial Intelligence | Automated testing | B testing | Bias detection | C# | CI/CD | Classification | Data Drift | Data Drift Detection | Data Pipelines | Databricks | Drift Detection | Error Rate Monitoring | Error rate | Experiment tracking | Explainability | FastAPI | Feature Engineering | Flask | GitHub | Java | LIME | Language Models | Language Processing | Large Language Models | Latency monitoring | MLflow | Machine Learning | Model Monitoring | Model versioning | Natural Language | Natural Language Processing | Optimization | Prediction Latency Monitoring | Prompt engineering | Python | RAG | REST API | REST API Authentication | REST APIs | Rate Limiting | Rate monitoring | Retrieval-Augmented Generation | SHAP | Semantic Search | Series forecasting | Supervised Learning | Time Series | Time Series Forecasting | TypeScript | Unsupervised Learning | Vector Databases | Weights and Biases
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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