Machine Learning Solutions Architect
Tasks
- Build and operate robust data pipelines
- Collaborate with data scientists on deployability at scale
- Create environments for data scientists to build models
- Define deployment approach and infrastructure for machine learning models
- Demonstrate business value of data and machine learning
- Design and deploy model retraining pipelines
- Design and implement machine learning inference solutions
- Develop and operate APIs and web server applications
- Ensure performance security scalability and maintainable integrations
- Extract customer data and load into analytical environments
- Implement model monitoring and QA testing
- Validate and test models in QA and production
- Write and optimize distributed SQL queries
Perks/Benefits
- 10 paid holidays
- 4 weeks PTO
- Advanced training and certifications
- Professional development
- Remote-first work environment
Skills/Tech-stack
APIs | AWS | AWS SageMaker | Amazon EMR | Amazon Redshift | Apache Spark | Azure Machine Learning | Data Pipelines | Databricks | Distributed Systems | Django | Docker | Flask | HDFS | Java | Keras | Kubernetes | Linux | MLflow | Machine Learning | Networking | PySpark | Python | SQL | Scala | Scikit-learn | Snowflake | Spring | TensorFlow
Education
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