Machine Learning Engineer | MLOps & Scalable Systems
PHOENIX, AZ, US, 85004-3903
USD 118K-190K (estimate) Senior-level Full Time
Tasks
- Architect low latency applications for streaming and high volume pipelines
- Collaborate with data scientists enterprise architects and product teams
- Design build deploy and monitor scalable reliable secure ML solutions
- Develop and deploy machine learning models and algorithms
- Gather and validate data requirements and performance checks
- Lead MLOps lifecycle for production machine learning systems
- Lead analytics initiatives and technical decisions on advanced analytics
- Manage ML lifecycle governance with CI CD monitoring testing and documentation
- Mentor and coach junior staff
- Perform predictive statistical modeling and experimental iterative validation
- Prepare integrate transform and analyze data for modeling
- Present findings and make business recommendations
- Utilize programming for data acquisition transformation and modeling
Perks/Benefits
Skills/Tech-stack
.NET | API | Amazon SageMaker | Apache Kafka | Apache Spark | Azure | C++ | CI/CD | Java | Kubeflow | MLOps | MLflow | Machine Learning | Model Monitoring | Model Testing | ODBC | Python | R | SQL
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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