Sr Machine Learning Engineer
Tasks
- Build automated ML pipelines training deployment monitoring retraining
- Build optimize ETL ELT workflows
- Build predictive classification recommendation NLP generative AI solutions
- Contribute to architecture decisions for ML platforms and data ecosystems
- Deploy manage models in cloud using containerization and orchestration
- Design build train validate optimize machine learning models
- Design develop scalable data pipelines ingestion transformation processing
- Develop data models curated datasets
- Develop reusable ML frameworks feature stores model serving architectures
- Ensure data quality lineage governance observability
- Ensure security privacy governance responsible AI compliance
- Establish engineering best practices coding standards governance frameworks
- Establish monitoring for model performance data drift operational health
- Evaluate emerging AI/ML technologies
- Implement CI CD for ML and data engineering workflows
- Maintain technical documentation support audit and compliance
- Mentor junior engineers and provide technical leadership
- Translate business requirements into scalable technical solutions
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | CI/CD | Data Drift | Data Drift Detection | Data Governance | Data Modeling | Data Pipelines | Data Quality | Docker | Drift Detection | ELT | ETL | Feature Stores | Generative AI | Git | Kubernetes | LLM | MLOps | Machine Learning | Model Deployment | Model Monitoring | Monitoring | NLP | PyTorch | Python | RAG | Retrieval-Augmented Generation | SQL | Scikit-learn | TensorFlow | Vector Databases
Education
N/A
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