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Contractual Artificial Intelligence Machine Learning Jobs

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Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... Artificial Intelligence (AI)/Machine Learning (ML) models Essential Duties & Responsibilities Research, analyze, support, and implement machine learning solutions on the Snowflake Cloud data ...

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Contractual Artificial Intelligence Machine Learning information

What is the difference between Contractual Artificial Intelligence Machine Learning vs Data Scientist?

AspectContractual Artificial Intelligence Machine LearningData Scientist
CredentialsRelevant degrees in CS, AI, ML; certifications in AI/ML toolsDegrees in CS, Statistics, Data Science; certifications in data analysis
Work EnvironmentProject-based, contractual roles often with tech firms or consultanciesFull-time or contract roles in various industries, including tech, finance, healthcare
Industry UsagePrimarily in AI/ML development projects, automation, and software firmsData analysis, modeling, and insights across multiple sectors

Contractual Artificial Intelligence Machine Learning specialists focus on developing AI and ML models on a contractual basis, often within tech or consulting firms. Data Scientists analyze data to generate insights, working across industries. While both roles require technical skills, AI/ML roles emphasize model development, whereas Data Scientists focus on data analysis and interpretation.

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Contractual Artificial Intelligence Machine Learning jobs near you
Infographic showing various Contractual Artificial Intelligence Machine Learning job openings in the United States as of July 2026, with employment types broken down into 80% Full Time, 16% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Artificial Intelligence/Machine Learning Engineer Specialist

Artificial Intelligence/Machine Learning Engineer Specialist

Connect Tech+Talent

Austin, TX • On-site, Remote

$113K - $136K/yr

Other

Posted 13 days ago

Job description

Job Description Artificial Intelligence/Machine Learning Engineer Specialist Austin, Texas (Hybrid OR Fully Remote) Contract (40 hours per week - 990 Hours) Minimum: 6+ Years - 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 6+ Years - 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 10+ Years - 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 6+ Years - 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 4+ Years - 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 micro-service deployment via Docker, AKS, and Git-based CI/CD 4+ Years - 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 Preferred: 4+ Years - Continuous data quality enforcement using Great Expectations and parameterized pytest suites; experience validating 100+ reconciliation rules on synthetic and production samples with automated regression coverage for SOX, PCI-DSS, or HIPAA-regulated audit environments 3+ Years - Legacy system data migration experience involving COBOL or mainframe source environments (AWS Glue, Redshift, or equivalent); aggregate validation checks, tolerance-threshold variance surfacing, and actuarial or regulatory sign-off workflows for government or healthcare modernization programs 3+ Years - Azure Purview data lineage and metadata management; Delta Lake compaction, ACID semantics, and Parquet optimization for downstream analytics; Azure Key Vault managed identity integration for encryption-in-transit and at-rest compliance across reconciliation artifacts

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