Python MLOps Engineer
Role details
Job location
Tech stack
Job description
Our client seeks a Python-heavy MLOps engineer to own coding, debugging, and maintenance for a fast-evolving pilot ML python application. The role focuses on backend Python and SQL in a lightly documented codebase, adjacent to machine learning without designing models. You will troubleshoot issues across code, data, and logic, implement business rule changes, and enhance logging to support downstream reporting. This work enables the senior data scientist to concentrate on model development while you drive stability and production-like support for the pilot., * Trace, analyze, and modify existing Python code within a changing pilot codebase.
- Write and update SQL queries for data retrieval and logic corrections.
- Debug issues reported by stakeholders and resolve defects in code and logic.
- Investigate unexpected or inconsistent model outputs to determine root causes.
- Implement business rule and logic changes safely and predictably.
- Add and enhance logging across the workflow to support observability and reporting.
- Provide production-like troubleshooting support for the pilot process.
- Identify root causes across code, data, logic, or model-adjacent behavior.
- Partner with stakeholders to understand requested changes and translate them into code.
- Ensure outputs and logs meet downstream reporting needs.
Requirements
- Strong Python development experience in backend or application logic environments.
- Strong SQL skills with the ability to write and modify complex queries.
- Demonstrated experience working within and extending existing codebases using version control such as GitHub.
- Proven debugging and troubleshooting ability in loosely documented, evolving systems.
- Experience supporting backend workflows and application logic with production-like support.
- Exposure to data science or machine learning applications sufficient to interpret model outputs and feature behavior.
- Experience with MLOps or model-adjacent systems (preferred).
- Experience with Google Cloud, Vertex AI, and BigQuery (preferred).
- Experience supporting data science workflows or applications, especially in fast-changing pilot environments (preferred).
Benefits & conditions
Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range.
W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick time if required by law in the worked-in state/locality.
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