Full-Stack AI Engineer
Tasks
- Automate data labeling and preprocessing
- Build ETL pipelines
- Build back end services and microservices
- Build front-end user interfaces
- Build vector search integrations
- Containerize ML services with Docker
- Deploy machine learning models
- Deploy services to Kubernetes
- Document systems for reproducibility
- Ensure AI data privacy compliance
- Implement CI/CD pipelines
- Implement access control and rate limiting
- Implement retrieval-augmented generation
- Integrate ML models with APIs
- Manage datasets in cloud warehouses
- Monitor model drift
- Monitor model latency and cost
- Productionize machine learning prototypes
- Secure API endpoints
Perks/Benefits
Skills/Tech-stack
API Security | Access Control | Airflow | Amazon Redshift | BigQuery | CI/CD | Dagster | Docker | ETL | Faiss | FastAPI | Flask | GDPR | HIPAA | Hugging Face | JavaScript | Kubeflow | Kubernetes | MLOps | MLflow | Microservices | Next.js | Node.js | OpenAI | Pinecone | Prefect | PyTorch | Python | RAG | Rate Limiting | React | Retrieval-Augmented Generation | SOC 2 | SOC2 | SQL | SageMaker | Serverless | Snowflake | TensorFlow | TypeScript | Vector Search | Vertex AI | Vue | Weaviate | Weights and Biases
Education
N/A
Roles
AI Engineer | Engineer | Full Stack | Full Stack AI Engineer | Software Engineer
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