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Apprentice Machine Learning Testing Jobs in Kissimmee, FL

Varsity Tutors

IBEW Tutor

Orlando, FL · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of IBEW apprenticeship aptitude test content covering reading comprehension ...

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Apprentice Machine Learning Testing information

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How much do apprentice machine learning testing jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for apprentice machine learning testing in Kissimmee, FL is $17.11, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $18.70 per hour, depending on experience, location, and employer.

What does an apprentice machine learning testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What kinds of projects or tasks can I expect to work on as an apprentice machine learning testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

What are the key skills and qualifications needed to thrive as an apprentice machine learning testing, and why are they important?

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

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Apprentice Machine Learning Testing jobs near you

Director, Data Science

SeaWorld Parks & Entertainment

Orlando, FL • On-site

Full-time

Re-posted 15 days ago

Job description

Job Summary:
SeaWorld Parks & Entertainment is a world-renowned leader in the themed-park and entertainment industry. They are seeking a Director of Data Science to develop and operationalize predictive models, build AI-driven learning tools, and drive marketing optimization strategies.
Responsibilities:
• Develop, test, and operationalize predictive and prescriptive models to enable right audience, right message, right channel marketing execution:
• Identify customers likely to purchase a Pass, Fun Card, Multi-Day, or Single-Day Ticket to optimize targeting and creative execution.
• Predict whether a guest is an Animal Lover, Thrill Seeker, or Foodie to tailor marketing creative, landing pages, and post-purchase engagement.
• Forecast LTV to inform Customer Acquisition Cost (CAC), prospect targeting, win-back strategies, and lapse/churn risk management.
• Build AI-driven learning tools to empower corporate and park teams with real-time, data-driven decision-making capabilities:
• Develop self-serve tools to measure the impact of marketing efforts, ticket pricing, and promotions on pass sales and visitation.
• Build models to assess offer impact by channel, optimize media mix, and forecast visitation based on geo-lift experiments.
• Create a real-time performance tracking system in Databricks, integrating spend, impressions, clicks, and purchases with:
• Automated anomaly detection triggering alerts when deviations exceed a set threshold from plan, last week, or year-over-year trends.
• Root cause diagnostics to enable teams to take immediate corrective action.
• Build a queryable platform that triangulates business results, marketing performance, surveys, and social listening, enabling teams to:
• Use natural language queries for insights.
• Support conversational commerce by analyzing web recordings, call center transcripts, and social forum discussions.
• Drive agentic AI exploration, testing, and productionalization to automate real-time marketing decisions and revenue strategies:
• Develop AI agents that adjust channel spend in real-time to meet pass/ticket and visit goals within budget constraints.
• Enable certain AI-driven offer optimizations to be auto-deployed, while others require human authorization.
• Forecast daily and next-day attendance and trigger geo-fenced, time-sensitive offers (e.g., 4 PM-to-close tickets, animal encounter day-of offers).
• Use contextual AI to auto-optimize email offers, messages, and images.
• Deploy generative AI to create dynamic content variations based on guest behavior and engagement.
Qualifications:
Required:
• Expertise in AI, machine learning, and predictive modeling with a track record of deploying real-time marketing optimization solutions.
• Strong experience with Databricks, Python, SQL, Spark, and cloud platforms (AWS/GCP).
• Ability to translate AI-driven insights into tangible business strategies that impact revenue and guest engagement.
• Experience in leading data science teams and collaborating with marketing, sales, and product teams.
• Strong understanding of media optimization, attribution modeling, and real-time decisioning AI.
Company:
SeaWorld Parks & Entertainment™ is a leading theme park and entertainment company providing experiences that matter and inspiring guests to protect animals and the wild wonders of our world. Founded in 1959, the company is headquartered in Orlando, USA, with a team of 10001+ employees. The company is currently Late Stage.

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