AI/ML Engineer
Tasks
- Automate AI ML data preparation and feature engineering
- Automate data integration between pilot and production
- Automate data transformation and normalization
- Automate repetitive technical tasks
- Collaborate with analysts to identify automation opportunities
- Create automation workflows for malware sample collection
- Develop automated data pipelines
- Document automation solutions and maintain code repositories
- Ensure data quality and integrity
- Implement AI/LLM integrations
- Implement API integrations for data sharing
- Implement monitoring and alerting automation
- Optimize automation performance and efficiency
- Scale automation from pilot to production
- Support Automated Malware Analysis platform development
- Support continuous improvement of automated capabilities
Perks/Benefits
- 401k matching
- Dental insurance
- Medical insurance
- Paid Holidays
- Paid time off
- Pet insurance
- Professional training
- Vision insurance
Skills/Tech-stack
API Integration | AWS | Airflow | Amazon Bedrock | Amazon Kinesis | Apache Spark | Automation frameworks | CI/CD | Data Engineering | Data Ingestion | Data Ingestion Pipelines | Data Modeling | Data Normalization | Data Transformation | Data platforms | Database systems | Databricks | Databricks AI | Docker | Feature Engineering | Git | Hadoop | Ingestion pipelines | Kafka | Kubernetes | LLM API | LLM API integration | Language Models | Large Language Models | Machine Learning | Prefect | Python | Streaming Data | Streaming Data Platforms | Version control | Workflow Orchestration
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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