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Senior Software Development Engineer
4 months ago
**This is a contracted role until 10/31/2024 with the potential to extend based on budgets and headcount. Full benefits are offered throughout the contract period including: Medical, Dental, Vision, Life Insurance.**
About The Team:
Data pipeline and ETL tooling are critical to making ML successful. Our unified platform simplifies development, enabling ML applications to be easily built, maintained, deployed, and validated. We focus on improving data pipeline and ETL tooling to drive high-value ML solutions efficiently. Our team is a diverse group of dedicated individuals committed to being relentlessly innovative, encouraging, and positive.
About the Role:
As a Software Development Engineer in ML, you will transition Databricks pipelines and notebooks to AWS tools, develop features promoting data mesh architecture, lead best practices in ML and ML Ops, influence product vision with your technical expertise, and provide critical feedback on technical designs and decisions. This is a hybrid position.
Responsibilities:
- Transition Databricks pipelines to AWS-based data engineering tooling.
- Transition Databricks notebooks to AWS SageMaker Studio.
- Develop features for data engineering tools that promote data mesh architecture principles.
- Lead teams in best practices for ML and ML Ops.
- Influence product vision and strategy with technical expertise.
- Provide feedback on technical designs, architecture, and decisions.
Requirements:
Basic Qualifications:
- 2+ years of experience with Databricks.
- 2+ years of experience with ML pipeline tools: Airflow, Dagster, ML Flow, AWS Glue, Spark, etc.
- 2+ years of experience with cloud compute technologies: AWS, GCP, etc.
- 5+ years of experience building production-grade software and practicing Agile methodologies.
Other Qualifications:
- 3+ years of experience building data mesh architectures.
- 3+ years of experience with ML Ops.
- 3+ years of experience with machine learning and data science technologies.
