AIML Oversight Specialist
Job Location:
Austin, TX - USA
Monthly Salary:
Posted on:
Vacancies:
Job Summary
Location : Austin TX (Hybrid)
Duration : Contract role (Part-time)
The client is looking to fill an AI/ML Oversight Specialist role. This specialist will act as an independent quality assurance expert within the RISE data migration program ensuring the AI capability layer delivers accurate consistent and auditable results. The ideal candidate must have a strong production engineering background to verify architectural decisions validate high-volume data pipeline integrity review pipeline code and optimize system performance alongside the engineering team. Additionally they will be responsible for documenting validation frameworks for future knowledge transfer and clearly communicating technical quality findings to non-technical stakeholders.
Required Experience Skills and Qualifications:
This role is for an AI/ML Oversight Specialist with a strong production software engineering background.
| Years | Skill/Experience |
| 2 | Production software engineering including: Python backend services async pipeline architecture and gRPC/REST API development. |
| 2 | Demonstrated ability to build ship and maintain systems at scale with measurable performance outcomes. |
| 2 | Regression testing framework design and execution. |
| 2 | Experience building automated test infrastructure that provides coverage across complex multi-system workflows including systems not accessible via standard DOM or API selectors. |
| 2 | High-volume data pipeline validation including batched ingestion bulk-load integrity verification record count reconciliation and exception identification across large structured datasets. |
| 1 | Clear technical communication of system behavior and quality findings to cross-functional teams including engineers product managers and non-technical stakeholders in a structured delivery environment. |
Preferred Experience Skills and Qualifications:
| Years | Skill/Experience |
| 2 | PostgreSQL query optimization bulk-load performance tuning and data integrity validation at scale; experience identifying and resolving data quality issues across high-volume ingestion and transformation pipelines. |
| 1 | Cross-team code review discipline with demonstrated ability to catch API contract issues performance regressions and data integrity risks before production; experience reviewing both backend and frontend pull requests across multi-engineer teams. |
| 1 | Experience in a production engineering environment requiring end-to-end ownership of quality outcomes across multiple product teams or customer-facing services; comfort operating across ambiguous fast-moving technical environments with high accountability. |
