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Oracle Machine Learning Jobs in California (NOW HIRING)

Pwc

ERP AI Engineer - Manager

Los Angeles, CA · On-site

$99K - $232K/yr

... Oracle Machine Learning. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and ...

Pwc

ERP AI Engineer - Manager

San Diego, CA · On-site

$99K - $232K/yr

... Oracle Machine Learning. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and ...

Pwc

ERP AI Engineer - Manager

San Francisco, CA · On-site

$99K - $232K/yr

... Oracle Machine Learning. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and ...

Pwc

ERP AI Engineer - Manager

Sacramento, CA · On-site

$99K - $232K/yr

... Oracle Machine Learning. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and ...

Pwc

ERP AI Engineer - Manager

Irvine, CA · On-site

$99K - $232K/yr

... Oracle Machine Learning. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and ...

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How much do oracle machine learning jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for oracle machine learning in California is $60.35, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $70.24 per hour, depending on experience, location, and employer.

What does an Oracle Machine Learning do?

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 Oracle Machine Learning?

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?

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.

What are popular job titles related to Oracle Machine Learning jobs in California? For Oracle Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Oracle Machine Learning jobs in California look for? The top searched job categories for Oracle Machine Learning jobs in California are:
Oracle Machine Learning jobs near you
Infographic showing various Oracle Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $125,519 per year, or $60.3 per hour.

Machine Learning Engineer - Product Marketing Customer Analytics

Apple

Cupertino, CA • On-site

Full-time

Re-posted 25 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

At Apple, new ideas have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! The Product Marketing Customer Analytics team is seeking a Machine Learning Engineer with deep technical experience in predictive analytics and analytic engineering.
Description
Support Product Marketing, Investor Relations, and the Executive Team with predictive analytics for customer product and services engagement. Understand product requirements then translate them into modeling tasks and engineering tasks
Develop scalable ML algorithms and models to understand customer behavior and provide leadership with actionable insights and recommendations
Design and implement end-to-end machine learning pipelines-from feature engineering to model serving- using best in class MLOps frameworks
Develop and optimize deep learning and traditional ML solutions on high-volume datasets using GPU clusters or distributed CPU environments.
Experiment with cutting-edge algorithms, providing advanced insights into customer behavior and engagement.
Manage ML projects through all phases, including data quality, algorithm/feature development, predictive modeling, visualization, and deployment and maintenance.
Tackle difficult, non-routine analysis/prediction problems, applying advanced ML methods as needed.
Partner with peers to build and prototype analysis pipelines that provide insights at scale.
Collaborate with data engineers and infrastructure partners to implement robust solutions and operationalize models. Enhance and evolve solutions to meet changing business needs with agility.
Minimum Qualifications
8+ years of hands-on programming skills for large-scale data processing
Graduate degree required in Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field
Preferred Qualifications
Excellent understanding of analytical methods and machine learning algorithms including regression, clustering, classification, optimization, and other advanced analytic techniques.
8+ years of proven experience building and scaling predictive models across distributed systems (eg: Spark, Kubernetes, GPU clusters), production model hosting, and handling end-to-end performance optimization to solve business problems.
8+ years of hands-on programming skills (Python, and/or Spark) for large-scale data processing, deriving key insights, developing machine learning models on structured and unstructured data, and with demonstrated success maintaining robust, high-throughput ML pipelines in a production environment.
Comfortable with advanced deep learning frameworks (Tensorflow, PyTorch) and adept at designing and scaling ML platforms that include feature stores, automated retraining pipelines and CI/CD integration. Able to design systems to handle high-volume ML workflows and implement scalable, fault-tolerant solutions.
Solid technical database and data modeling knowledge (Oracle, Hadoop, SnowFlake), and experience optimizing SQL queries on large dataset for performance-critical analytics.
Able to work effectively on ambiguous data and constructs within a fast-changing environment, tight deadlines and priority changes
Strong communication skills and ability to explain complex technical topics to both data science peers and non-technical business stakeholders, effectively presenting findings and recommendations to senior executives.
Demonstrated success in partnering cross-functionally, guiding diverse technical teams, aligning business stakeholders, invested in collective success of teams and project outcomes.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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