Machine Learning Engineer
Tasks
- Apply MLOps best practices
- Build reproducible ML workflows for data preparation training evaluation and inference
- Deliver compliant scalable ML powered services
- Design implement and maintain production ML solutions
- Implement monitoring and evaluation frameworks
- Improve AI assisted software delivery lifecycle
- Improve data quality model performance latency and cost
- Own SLAs on call incident response customer feedback triage and post mortems
- Perform code reviews and automated testing
- Translate business problems into measurable ML problem statements
Perks/Benefits
- Generous time off
- Healthcare
- Paid parental leave
- Paid personal time off
- Paid sick time
- Parental leave
- Remote-first work environment
- Retirement savings program
- Wellness leave
Skills/Tech-stack
AWS | Airflow | Argo CD | Azure | CI/CD | Docker | DynamoDB | EMR | Feature Store | Flink | GCP | Git | GitOps | Java | Kafka Streams | Kubeflow | Kubernetes | LLM | LLMOps | Langchain | Langgraph | MLOps | MLflow | Machine Learning | Metaflow | Model Evaluation | Model Observability | OpenSearch | Optimization | Probability | Python | RAG | SQL | SageMaker | Snowflake | Spark | Statistics | Vector Databases | Vector Search
Education
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