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Apprentice Machine Learning Testing Jobs in Tulsa, OK

AI Engineer

Tulsa, OK · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... testing, and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output ...

New

Data Science Tutor

Tulsa, OK · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... testing, validation, and operational excellence - Establish and drive consistent quality control ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... Responsibilities - Apply automated testing and governance controls effectively - Analyze complex ...

Research and evaluate emerging AI technologies, including generative AI and machine learning applications, to support business innovation * Contribute to the evaluation, testing, and adoption of ...

Research and evaluate emerging AI technologies, including generative AI and machine learning applications, to support business innovation * Contribute to the evaluation, testing, and adoption of ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... testing strategies - Architecting, building, and deploying conversational bots using Azure Bot ...

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Apprentice Machine Learning Testing information

See Tulsa, OK salary details

$10

$17

$25

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

As of Jul 29, 2026, the average hourly pay for apprentice machine learning testing in Tulsa, OK is $17.68, according to ZipRecruiter salary data. Most workers in this role earn between $14.95 and $19.33 per hour, depending on experience, location, and employer.

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 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 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.

What are popular job titles related to Apprentice Machine Learning Testing jobs in Tulsa, OK? For Apprentice Machine Learning Testing jobs in Tulsa, OK, the most frequently searched job titles are:
Infographic showing various Apprentice Machine Learning Testing job openings in Tulsa, OK as of July 2026, with employment types broken down into 89% Full Time, 10% Part Time, and 1% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $36,779 per year, or $17.7 per hour.

AI Engineer

Pwc

Tulsa, OK • On-site

$50K - $112K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

New


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 76 frontline employees who took The Breakroom Quiz

24th of 73 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

IFS - Information Technology (IT)

Management Level

Associate

Job Description & Summary

The Opportunity
As an AI Engineer, you will be at the forefront of transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Within our Internal Firm Services practice, you will apply data, algorithms, and software engineering to build and deploy software and platform systems that create Artificial Intelligence and Machine Learning-based solutions at scale. Your work will involve designing AI systems, data wrangling, and software implementation to enable the AI models to be useful and scalable.
As an Associate, you will focus on learning and contributing to projects while developing your skills and knowledge to deliver quality work. You will engage with different stakeholders to build meaningful connections, learn how to manage and inspire others, and grow your personal brand by deepening your technical knowledge of firm services and technology resources. In increasingly complex situations, you will build acumen to anticipate the needs of your teams and internal stakeholders, embrace ambiguity, ask questions, and use these challenges as opportunities for growth.
In this role, you will take ownership and consistently deliver quality work that drives value for our clients and success as a team. You will be part of a dynamic environment where every experience is an opportunity to learn and grow, opening doors to more opportunities within the firm.
Responsibilities
- Designing and implementing AI systems to transform raw data into actionable insights
- Developing scalable machine learning models using Python and TensorFlow
- Integrating data from various sources to create unified views for analysis
- Building and maintaining data pipelines to support AI model deployment
- Applying complex data analysis techniques to discern patterns and trends
- Collaborating with team members to enhance AI solutions and drive business growth
- Utilizing natural language processing tools like NLTK for text analytics and sentiment analysis
- Implementing neural networks and deep learning methods for advanced AI applications
- Managing data quality and infrastructure to support reliable AI operations
- Engaging in continuous learning to adapt to new technologies and methodologies in AI engineering
What You Must Have
- At least a Bachelor's degree or, in lieu of a degree, demonstrating in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in Engineering with AI and Machine Learning for each missing year of college is required
- At least 1 years of experience
What Sets You Apart
- In at least one of the following fields of study: Computer and Information Science, Computer Engineering, Computer Management, Management Information Systems, Information Technology
- At least one of the following: Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials

- Building and orchestrating AI agent workflows using frameworks such as LangGraph to automate multi-step reasoning, integrate tools and APIs, and deliver scalable, context-aware solutions
- Applying generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models
- Developing automated evaluation frameworks, including LLM-as-judge pipelines, regression testing, and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output groundedness
- Optimizing open-weight language models, including LLaMA, Mistral, and Gemma, for local and cloud deployment using quantization, inference acceleration, and model-routing techniques
- Designing agent harnesses and implementing context engineering, memory management, retry logic, and structured output validation to support reliable, multi-step AI workflows
- Demonstrating proficiency in Python and TensorFlow for AI projects
- Utilizing machine learning libraries like Scikit-Learn for data analysis
- Engaging in complex data analysis and pattern recognition
- Implementing AI solutions using open-source software
- Applying natural language processing techniques in real-world applications

Travel Requirements

Up to 20%

Job Posting End Date

The salary range for this position is: $50,500 - $112,500. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines

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