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Machine Learning Engineer Opt Jobs in Oklahoma (NOW HIRING)

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

New

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

New

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

New

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

New

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

New

... for machine learning pipelines, feature engineering, and model lifecycle management - Implements model monitoring, performance validation, traceability, and reproducibility of AI artifacts ...

New

$13 - $17.50/hr

Here at Strayos, we use advanced computer vision and machine learning on images and machine sensors ... Engineering, Physics, Computer Science or a related field, within 1 year of completion.

US Tech - AI Engineering Manager

Tulsa, OK · On-site

$73.50K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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Machine Learning Engineer Opt information

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are popular job titles related to Machine Learning Engineer Opt jobs in Oklahoma? For Machine Learning Engineer Opt jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Oklahoma look for? The top searched job categories for Machine Learning Engineer Opt jobs in Oklahoma are:
What cities in Oklahoma are hiring for Machine Learning Engineer Opt jobs? Cities in Oklahoma with the most Machine Learning Engineer Opt job openings:
US Tech - AI Engineering Senior Associate

US Tech - AI Engineering Senior Associate

Pwc

Oklahoma City, OK

$55K - $187K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 20 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 73 frontline employees who took The Breakroom Quiz

20th of 57 rated business consultants


Job description

Industry/Sector

Not Applicable

Specialism

Data Science

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.
Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn't clear, you ask questions, and you use these moments as opportunities to grow.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Respond effectively to the diverse perspectives, needs, and feelings of others.
Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
Use critical thinking to break down complex concepts.
Understand the broader objectives of your project or role and how your work fits into the overall strategy.
Develop a deeper understanding of the business context and how it is changing.
Use reflection to develop self awareness, enhance strengths and address development areas.
Interpret data to inform insights and recommendations.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
The Opportunity
As part of the People Tech & AI team you will develop, test, and validate Generative AI agents and data pipelines, promoting reliability, scalability, and alignment with PwC standards. As a Senior Associate you will analyze complex problems, mentor others, and maintain elevated standards while collaborating with multidisciplinary teams to support AI-enabled client solutions. This position provides an exciting opportunity to enhance your skills in automated testing and governance controls while contributing to innovative AI-driven solutions.
Responsibilities
- Apply automated testing and governance controls effectively
- Analyze complex issues and provide actionable insights
- Mentor and guide junior associates in their tasks
- Uphold rigorous standards of quality and technical excellence
What You Must Have
- Bachelor's Degree in Computer Science, Data Processing/Analytics/Science
- At least 2 years of experience in data engineering, AI/ML engineering, or quality engineering
- In lieu of a Bachelor's 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 technology for each missing year of college
What Sets You Apart
- Demonstrating three years of specialized training in technology preferred
- Experience with test automation and CI/CD pipelines
- Familiarity with LLMs and prompt engineering concepts
- Understanding enterprise data patterns and quality frameworks
- Building and maintaining automated test suites for AI agents
- Validating integrations with Power Automate platform
- Executing LLM evaluation frameworks using defined metrics
- Working with data scientists and ML engineers
- Upholding professional standards and documentation expectations

Travel Requirements

Up to 20%

Job Posting End Date

The salary range for this position is: $55,000 - $151,470. For residents of Washington state the salary range for this position is: $55,000 - $187,000. 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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