Engineer - Data Science
Tasks
- Automate detection root cause analysis
- Build deep learning models
- Create technical design documents
- Deploy and version models
- Detect drift and bias
- Develop machine learning models
- Expose ml ai capabilities via apis
- Fine-tune language models
- Implement LLMOps pipelines
- Implement MLOps pipelines
- Mentor junior engineers
- Perform data preparation and feature engineering
- Set up model monitoring and observability
- Validate experiment and benchmark models
Perks/Benefits
- N/A
Skills/Tech-stack
AIOps | API Integration | Amazon SageMaker | Anomaly Detection | Authentication | Bias detection | CI/CD | Cloud Computing | Cost Optimization | Data Pipelines | Deep learning | Docker | Drift Detection | Embeddings | Feature Engineering | Fine Tuning | Governance | Kubeflow | Kubernetes | LLM | Latency monitoring | MLflow | Machine Learning | Microservices | Model Serving | Monitoring | NumPy | Observability | Pandas | Prompt engineering | PyTorch | Python | RAG | Rate Limiting | Scikit-learn | Series analysis | Telemetry data | TensorFlow | Time Series | Time Series Analysis | Vector Databases | Vertex AI
Education
Bachelor of Arts | Bachelor of Engineering | Bachelor of Science
Regions
Countries
States
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