Senior AI/ML & Data Engineer
Tasks
- Architect LLM enabled application target state
- Architect data lakes and warehouses
- Build automated ETL and ELT data pipelines
- Build retrieval-augmented generation pipelines
- Create scalable machine learning pipelines
- Define AI requirements and roadmaps
- Design and deploy machine learning models
- Design embedding and prompt architectures
- Develop Agentic AI systems
- Develop LLM applications
- Develop MLOps solutions
- Implement CI CD for machine learning
- Implement data preprocessing training and evaluation workflows
- Implement data quality validation frameworks
- Produce architecture diagrams and interface specifications
- Set up model monitoring logging and drift detection
- Translate business problems into AI solutions
Perks/Benefits
- N/A
Skills/Tech-stack
800-53 | AWS | Amazon SageMaker | Anthropic | Azure | Azure Machine Learning | BigQuery | CI/CD | CloudFormation | Data Lakes | Data Quality | Data Validation | Data Warehousing | Databricks | Docker | Drift Detection | ELT | ETL | Embeddings | FedRAMP | GCP | GitLab | Huggingface | Jenkins | Kubernetes | Logging | MLOps | Machine Learning | Microservices | Model Monitoring | Model versioning | NIST 800 | NIST 800-53 | OpenAI | Prompt engineering | PyTorch | Python | REST APIs | Ray | Retrieval-Augmented Generation | Scikit-learn | Security Compliance | Snowflake | TensorFlow | Terraform | Vector Databases | Zero Trust
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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