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Oracle Machine Learning Jobs (NOW HIRING)

My3Tech

Machine Learning / AI Engineer

Austin, TX · On-site

Machine Learning / AI Engineer Location: Hybrid(Austin, TX) Duration: 12 Months The client is ... Oracle including stored procedures, partition switching, columnstore indexing, and query ...

New

phData

OR

... Oracle, and SAP; proven experience deploying machine learning models in production environments. * Strong working knowledge of SQL and the ability to write, debug, and optimize complex and ...

WireScreen

Machine Learning Engineer

New York, NY · On-site

$150K - $195K/yr

... and Oracle. We launched just three years ago and already have strong traction with top-tier ... As a Machine Learning Engineer at WireScreen, you will be working across our data systems to unlock ...

New

J5 Consulting

Machine Learning Engineer

Herndon, VA · On-site

$117K - $141K/yr

They are seeking a Machine Learning Engineer to provide analytical support for compliance with ... g., Oracle, MySQL, PostgreSQL, SQL, NOSQL, and/or structured and unstructured data) • ...

Deloitte

Oracle Gen AI Manager

Detroit, MI

Deloitte Oracle Generative AI Architect Managers help clients delineate strategy and vision, design ... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ...

Deloitte

Oracle Gen AI Manager

San Jose, CA

Deloitte Oracle Generative AI Architect Managers help clients delineate strategy and vision, design ... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ...

Deloitte

Oracle Gen AI Manager

Austin, TX

Deloitte Oracle Generative AI Architect Managers help clients delineate strategy and vision, design ... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ...

Deloitte

Oracle Gen AI Manager

Chicago, IL

Deloitte Oracle Generative AI Architect Managers help clients delineate strategy and vision, design ... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ...

Deloitte

Oracle Gen AI Manager

Arlington, VA · On-site

Deloitte Oracle Generative AI Architect Managers help clients delineate strategy and vision, design ... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ...

Deloitte

Oracle Gen AI Manager

Houston, TX

Deloitte Oracle Generative AI Architect Managers help clients delineate strategy and vision, design ... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ...

Deloitte

Oracle Gen AI Manager

Nashville, TN

Deloitte Oracle Generative AI Architect Managers help clients delineate strategy and vision, design ... machine learning initiatives * Identify high-value AI use cases and guide teams on prompt ...

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Oracle Machine Learning information

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How much do oracle machine learning jobs pay per hour?

As of Jun 28, 2026, the average hourly pay for oracle machine learning in the United States is $61.15, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $71.15 per hour, depending on experience, location, and employer.

What are the typical responsibilities and daily tasks of someone working in an Oracle Machine Learning position?

Professionals in Oracle Machine Learning roles are typically responsible for building, deploying, and optimizing machine learning models within Oracle Database environments. Daily tasks may include preparing and cleaning large data sets, developing algorithms using SQL, Python, or R, and interpreting results to provide actionable business insights. They often collaborate closely with data engineers, business analysts, and IT teams to understand data needs and translate business requirements into technical solutions. The role also involves monitoring model performance and making continuous improvements to ensure accuracy and efficiency. This position is dynamic and offers opportunities for ongoing learning and career growth in both data science and enterprise database management.

What are the key skills and qualifications needed to thrive in the Oracle Machine Learning position, and why are they important?

To thrive in an Oracle Machine Learning role, you need a strong foundation in machine learning algorithms, data analysis, and proficiency with Oracle Database and PL/SQL, typically supported by a degree in computer science, data science, or a related field. Experience with Oracle Machine Learning tools (such as OML4SQL or OML4Py), certifications like Oracle Certified Professional, and familiarity with platforms such as Oracle Cloud Infrastructure are highly valuable. Excellent problem-solving abilities, attention to detail, and effective communication skills help professionals collaborate across multidisciplinary teams. These competencies are crucial for designing predictive models, extracting meaningful insights from large datasets, and driving data-driven business decisions using Oracle technologies.

What is an Oracle Machine Learning job?

An Oracle Machine Learning job involves using Oracle's machine learning tools and databases to develop, deploy, and manage predictive models and AI-driven solutions. Professionals in this role work with SQL, Python, and Oracle Machine Learning (OML) to analyze data, automate processes, and optimize decision-making. Responsibilities may include data preparation, model training, and integrating machine learning models into Oracle databases and applications. This role is common in industries like finance, healthcare, and retail, where data-driven insights improve business outcomes. Strong knowledge of Oracle Cloud Infrastructure (OCI) and database management is often required.

More about Oracle Machine Learning jobs
What cities are hiring for Oracle Machine Learning jobs? Cities with the most Oracle Machine Learning job openings:
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Oracle Machine Learning jobs near you
Infographic showing various Oracle Machine Learning job openings in the United States as of June 2026, with employment types broken down into 4% As Needed, 80% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,184 per year, or $61.1 per hour.

Machine Learning / AI Engineer

Digerati Systems Inc.

Austin, TX • On-site

Other

Posted 2 days ago

Job description

Machine Learning / AI Engineer

Location: Austin, Texas - Hybrid or Remote


**This role can be hybrid or remote**

JOB DESCRIPTION

The client is seeking a Senior Machine Learning / AI Engineer with over 12 years of production experience to design, build, and maintain an AI-driven data reconciliation and analytics pipeline for the RISE data migration program. Operating within a highly regulated Azure environment (SOX, PCI-DSS, HIPAA), the ideal candidate will develop auditable anomaly detection, exception classification workflows, and LLM-evaluation frameworks to accelerate data conversion and provide real-time quality metrics for leadership. Beyond technical deployment, this role requires excellent communication skills to translate complex AI outputs for finance, risk, and program stakeholders, alongside a commitment to providing comprehensive technical documentation and knowledge transfer to embedded staff.


Minimum Requirements

This role is for a Machine Learning / AI Engineer with applied research experience in LLM pipeline development, model

evaluation, and intelligent automation.


Years Skill/Experience

6+ 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+ 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+ 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+ 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+ 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.

4+ 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 Requirements

Years Skill/Experience

4+ 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+ 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+ 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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