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Remote Machine Learning Quant Jobs in Texas (NOW HIRING)

AI Engineer

Austin, TX ยท On-site +1

$140K - $200K/yr

Remote (United States) Compensation: $140,000 - $200,000 base Visa Sponsorship: None available ... About the Role As an AI Engineer, you will design, train, and deploy machine learning models and ...

Demonstrated experience using machine learning, deep learning, statistical methodology, and ... Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills

Modeling Scientist

Houston, TX ยท On-site +1

$100K - $160K/yr

Working at the intersection of statistics, machine learning, and process-based ecosystem modeling ... quantitative field Responsibilities: * Generate and apply a model traceability framework for ...

Data Scientist

Austin, TX ยท On-site +1

Create predictive models and machine-learning algorithms * Modify and combine different models ... quantitative field is preferred * Must be a U.S. Citizen

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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Remote Machine Learning Quant information

What is the difference between Remote Machine Learning Quant vs Remote Data Scientist?

AspectRemote Machine Learning QuantRemote Data Scientist
Required CredentialsAdvanced degrees in quantitative fields, certifications in machine learning or financeDegrees in data science, statistics, or related fields; certifications like CAP or DASCA
Work EnvironmentFinancial firms, hedge funds, or quantitative trading companiesTech companies, research institutions, or consulting firms
Industry UsageFinance, trading, hedge fundsTechnology, healthcare, marketing, finance
Common Search/ComparisonYesNo

Remote Machine Learning Quants focus on developing quantitative models for trading and investment strategies within financial firms, often requiring finance-specific knowledge. Remote Data Scientists work across various industries, applying data analysis and machine learning to solve diverse business problems. While both roles involve machine learning, Quants are more finance-oriented, whereas Data Scientists have broader industry applications.

What are the most commonly searched types of Machine Learning Quant jobs in Texas? The most popular types of Machine Learning Quant jobs in Texas are:
What job categories do people searching Remote Machine Learning Quant jobs in Texas look for? The top searched job categories for Remote Machine Learning Quant jobs in Texas are:
What cities in Texas are hiring for Remote Machine Learning Quant jobs? Cities in Texas with the most Remote Machine Learning Quant job openings:
Artificial Intelligence/Machine Learning Engineer Specialist

Artificial Intelligence/Machine Learning Engineer Specialist

Connect Tech+Talent

Austin, TX โ€ข On-site, Remote

$113K - $136K/yr

Other

Posted 16 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