Director, AI Engineering (Data Science)
Columbia, MD, United States
USD 180K-240K Executive-level Full Time
Tasks
- Build data pipelines for large-scale datasets
- Create CI CD for ML
- Define AI roadmap
- Deploy models to production
- Design custom transformer architectures
- Drive reproducible experimentation
- Establish engineering best practices
- Implement model governance and compliance
- Implement monitoring drift detection retraining
- Lead client technical discovery and solutioning
- Lead cloud model deployment and infrastructure
- Lead feature engineering and model development
- Lead technical strategy and architecture
- Mentor and manage AI ML teams
- Oversee data science workflows
- Own AI model development lifecycle
- Present model results to executives
- Support RFP responses and proposals
- Validate models and run A B testing
Perks/Benefits
- 401k
- Commuter benefits
- Dental insurance
- Disability coverage
- Employee assistance program
- Life insurance
- Medical insurance
- Paid Holidays
- Paid time off
- Spending accounts
- Vision insurance
Skills/Tech-stack
A/B | A/B Testing | AWS SageMaker | Attention Mechanisms | Automated retraining | Azure Machine Learning | B testing | BERT | BigQuery | CI/CD | Causal Inference | DVC | Data Pipelines | Databricks | Deep learning | Docker | Drift Detection | Experiment tracking | Explainable AI | Feature Engineering | Flink | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | HuggingFace Transformers | Kafka | Kubernetes | LLMs | LightGBM | MLOps | MLflow | Machine Learning | Model Drift | Model Drift Detection | Model Governance | Model Monitoring | Positional encoding | PyTorch | Python | Responsible AI | SQL | Scikit-learn | Snowflake | Spark | Statistical modeling | T5 | TabTransformer | TensorFlow | Tokenization | Transformers | Vertex AI | Weights and Biases | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Language: en
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