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Remote Senior Machine Learning Engineer Jobs in Oklahoma

CCT

Machine Learning Engineer (AWS)

Tulsa, OK · On-site +1

Summary We're looking for a Machine Learning Engineer to design, deploy, and operate production ML systems on Amazon Web Services. You'll own the full lifecycle in a real-world, high-stakes ...

Varsity Tutors

Machine Learning Tutor

Oklahoma City, OK · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Tulsa, OK · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Stillwater, OK · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Centric Consulting

Okta AI Sr. Engineer

Saint Louis, OK · Remote

$47 - $60.75/hr

The AI identity engineer is responsible for applying artificial intelligence and machine learning ... Remote and Hybrid Work * Time Off When You Need It * Benefits That Flex * Professional Development ...

Strayos

$13 - $17.50/hr

... machine learning, remote sensing, geoscience, and physics. As an intern, you will learn how to ... Engineering, Physics, Computer Science or a related field, within 1 year of completion.

micro1 AI

Domain Expert - (STEM PhD)

Oklahoma City, OK · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

micro1 AI

Domain Expert - (STEM PhD)

Tulsa, OK · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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Remote Senior Machine Learning Engineer information

How do Remote Senior Machine Learning Engineers typically collaborate with cross-functional teams despite working remotely?

Remote Senior Machine Learning Engineers often work closely with data scientists, product managers, and software engineers using digital collaboration tools such as Slack, Jira, and video conferencing platforms. Regular virtual meetings and code reviews are standard practices to ensure alignment on project goals and to facilitate knowledge sharing. Clear communication, proactive documentation, and adaptability to different time zones are key to effective teamwork in a remote environment. This structure allows for flexibility while maintaining strong collaboration and project momentum.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually, often including bonuses and stock options. Such compensation typically requires a strong educational background, a track record of impactful projects, and expertise in tools like TensorFlow or PyTorch.

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

AspectRemote Senior Machine Learning EngineerRemote Data Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds statistical models, provides insights
Employer & Industry UsageTech companies, startups, AI-focused firmsResearch institutions, tech companies, finance, healthcare

Remote Senior Machine Learning Engineers focus on designing, building, and deploying ML models, often working closely with engineering teams. Data Scientists analyze data and develop insights, but may not always deploy models. Both roles require strong technical skills and are highly sought after in tech industries, but their core responsibilities differ.

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

To thrive as a Remote Senior Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, and strong programming skills (often in Python or similar languages), typically supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data engineering pipelines are commonly required, along with certifications like TensorFlow Developer or AWS Machine Learning Specialty. Excellent problem-solving, communication, and self-management skills help you collaborate remotely, lead projects, and explain complex models to stakeholders. These skills and qualities are vital for building scalable ML solutions, ensuring effective teamwork across distributed environments, and delivering impactful results.

What does a Remote Senior Machine Learning Engineer do?

A Remote Senior Machine Learning Engineer designs, develops, and deploys machine learning models and systems while working from a location outside the traditional office. They collaborate with cross-functional teams, analyze large datasets, build scalable algorithms, and often mentor junior engineers. Their work helps organizations automate processes, gain insights, and improve products or services using data-driven approaches. Senior engineers are also responsible for ensuring model performance, reliability, and integration into production environments. Working remotely, they use various communication and collaboration tools to stay connected with their team.

What engineers make $300,000 a year?

Senior machine learning engineers can earn $300,000 or more annually, especially with extensive experience, advanced skills in deep learning and data modeling, and work at large tech companies or in specialized industries. Compensation often includes base salary, bonuses, and stock options, particularly in high-demand markets.

Will MLE be replaced by AI?

As a Senior Machine Learning Engineer, the role involves designing, developing, and maintaining AI systems, which currently require human expertise. While AI tools can automate certain tasks, the need for skilled professionals to interpret data, ensure ethical use, and improve models remains essential. AI is more likely to augment rather than replace the responsibilities of MLEs in the foreseeable future.

What engineers make $200,000 a year?

Senior machine learning engineers often earn $200,000 or more annually, especially with extensive experience, advanced skills in deep learning and data modeling, and proficiency with tools like TensorFlow or PyTorch. Compensation can vary based on industry, location, and company size, with some roles in tech giants or specialized fields reaching or exceeding this level.
What are popular job titles related to Remote Senior Machine Learning Engineer jobs in Oklahoma? For Remote Senior Machine Learning Engineer jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Remote Senior Machine Learning Engineer jobs in Oklahoma look for? The top searched job categories for Remote Senior Machine Learning Engineer jobs in Oklahoma are:
What cities in Oklahoma are hiring for Remote Senior Machine Learning Engineer jobs? Cities in Oklahoma with the most Remote Senior Machine Learning Engineer job openings:
Remote Senior Machine Learning Engineer jobs near you
Infographic showing various Remote Senior Machine Learning Engineer job openings in Oklahoma as of July 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 100% Remote job distribution.
Machine Learning Engineer (AWS)

Machine Learning Engineer (AWS)

CCT

Tulsa, OK • On-site, Remote

Full-time

Re-posted 13 days ago

Job description

Summary
We're looking for a Machine Learning Engineer to design, deploy, and operate production ML systems on Amazon Web Services. You'll own the full lifecycle in a real-world, high-stakes environment - from training and packaging through deployment, monitoring, retraining, security, and cost control.
This role sits at the intersection of ML engineering and MLOps and is core to CCT's analytics strategy. You'll partner closely with data scientists, engineers, and product stakeholders to turn complex time-series and transactional data into reliable, observable, and cost-effective ML services that our customers can trust.
You'll thrive here if you naturally dig into why models behave the way they do, enjoy tracing issues to their root cause, and like collaborating across disciplines to ship robust systems that are built to last.
What You'll Do
  • Build and maintain reproducible model training workflows on AWS (SageMaker, S3, Glue, etc.), making retraining, rollback, and experimentation routine rather than heroic.
  • Deploy and operate real-time and batch inference services with full CI/CD pipelines, versioning, and safe rollout strategies (canary, shadow, A/B) so changes are deliberate and observable.
  • Instrument production models for performance, data drift, latency, and errors - and automate retraining triggers when models drift out of tolerance.
  • Maintain model lineage, auditability, and traceability to meet the compliance, governance, and reporting needs of the regulated gaming industry.
  • Enforce least-privilege IAM, encryption, and secure data access patterns across the entire ML platform.
  • Treat cost as a first-class engineering metric - right-size infrastructure, balance batch vs. real-time workloads, and continually reduce platform spend without sacrificing reliability.
  • Collaborate with engineers, data scientists, and product teams to translate business problems into ML solutions, communicate tradeoffs clearly, and iterate based on feedback.
  • Continuously explore new AWS services, ML frameworks, and deployment patterns to improve reliability, observability, and developer velocity on the ML platform.

Requirements
  • 3+ years of experience in machine learning engineering, MLOps, or a closely related discipline.
  • Hands-on experience with AWS ML and data services - SageMaker (training, endpoints, pipelines), S3, Lambda, Step Functions, CloudWatch, MWAA (Apache Airflow).
  • Experience working with time series data, including feature engineering, seasonality handling, and temporal train/test splits.
  • Strong Python skills and familiarity with common ML frameworks (scikit-learn, PyTorch, XGBoost, or equivalent).
  • Experience building and maintaining CI/CD pipelines for ML systems.
  • Demonstrated ability to monitor and debug production ML systems - latency, drift, errors, and data quality - and drive issues to root cause.
  • Comfort with SQL and working with structured data at scale.
  • Able to work collaboratively across teams, assume positive intent, and communicate clearly with both technical and non-technical stakeholders.
  • Track record of self-directed learning and technical growth in areas like AWS, ML frameworks, or deployment patterns.

Certified Banana Picker
Nice to Have
  • Experience in a regulated industry (gaming, finance, healthcare) where auditability, explainability, and compliance are first-class concerns.
  • Familiarity with feature stores, model registries, or ML metadata tools (e.g., MLflow, SageMaker Model Registry).
  • Experience with infrastructure-as-code (Terraform, CDK, or CloudFormation).
  • Exposure to data drift detection libraries or custom drift monitoring implementations.

Success Looks Like
  • Production models run reliably with clear, measurable business impact for casino operators.
  • Failures are observable, recoverable, and explainable - with logs, metrics, and traces that tell the full story.
  • ML systems scale predictably with usage and data volume, without runaway cost.
  • The ML platform becomes a trusted, well-understood part of CCT's product ecosystem - for both internal teams and external customers.

About CCT
CCT is the creator of Casino Insight™, the award-winning platform trusted by more than 350 casinos worldwide to automate cage operations, revenue audits, and operational analysis. Since 2012, Casino Insight has helped casinos replace manual work with streamlined workflows, improving accuracy, compliance, and profitability.
Headquartered in Tulsa, Oklahoma, CCT integrates seamlessly with leading casino management, hospitality, and financial systems-delivering measurable ROI and empowering teams to work smarter at every level.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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