AI/ML Engineer (Local to Texas Candidates)
Posted 1 day ago by Unique System Skills LLC
Negotiable
Undetermined
Remote
Remote
Summary: The role of AI/ML Engineer is focused on developing and deploying AI/ML pipelines for large-scale data reconciliation programs, specifically targeting candidates located in Texas. The position requires extensive experience with Azure data platforms and advanced SQL development, along with a strong background in anomaly detection and automated validation logic. This is a 12-month contract position with remote working arrangements. Candidates are encouraged to submit their resumes if interested.
Key Responsibilities:
- Develop and deploy applied AI/ML pipelines for large-scale data reconciliation programs.
- Engineer Azure data platforms including Azure Databricks, Azure Data Factory, and Azure Synapse Analytics.
- Perform advanced T-SQL and PL/SQL development across SQL Server and Oracle.
- Construct rule-based exception classification pipelines and prioritized work queues.
- Engineer cloud-native ingestion pipelines using Azure Data Factory and Azure Functions.
- Monitor production models and detect drift using Azure Monitor metrics.
Key Skills:
- Experience with PyTorch, Scikit-learn, and Azure Machine Learning.
- Proficiency in Azure data platform engineering.
- Advanced T-SQL and PL/SQL development skills.
- Ability to translate stakeholder control scenarios into automated validation logic.
- Experience with cloud-native ingestion pipeline engineering.
- Knowledge of production model monitoring and drift detection.
Salary (Rate): undetermined
City: undetermined
Country: undetermined
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
We have an opening for AI/ML Engineer with Remote (Local to Texas Candidates). Kindly send your updated resume if you are interested. Please find the job details below:
Position: AI/ML Engineer with Remote
Location: Remote (Local to Texas Candidates)
Duration: 12 Months Contract Position
Description:
Years | Skills/Experience |
| Applied AI/ML pipeline development and deployment for large-scale data reconciliation programs; production experience building anomaly-detection, root-cause analysis, and exception classification models using PyTorch, Scikit-learn, and Azure Machine Learning in regulated financial or government environments |
| Azure data platform engineering including Azure Databricks, Azure Data Factory, Azure Synapse Analytics, and Delta Lake; demonstrated ability to design automated, auditable reconciliation workflows eliminating manual row- and aggregate-level validation across multi-terabyte datasets |
| Advanced T-SQL and PL/SQL development across SQL Server and Oracle including stored procedures, partition switching, columnstore indexing, and query optimization sustaining sub-second query response for high-volume ETL and dashboard workloads |
| Rule-based exception classification pipelines and prioritized work queue construction; experience translating 30+ stakeholder control scenarios (finance, actuarial, risk) into automated validation logic, acceptance criteria, and agile backlog items |
| Cloud-native ingestion pipeline engineering with Azure Data Factory, Azure Service Bus, and Azure Functions; schema validation, data lineage management with Azure Purview, and containerized microservice deployment via Docker, AKS, and Git-based CI/CD |
| Production model monitoring and drift detection using Azure Monitor metrics and custom drift detectors; MLflow experiment tracking and gradient-boosting ensemble tuning ensuring validation models retain statistical power across evolving data volumes and product mixes |