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Remote Machine Learning Engineer Jobs in Tulsa, OK

CCT

Machine Learning Engineer (AWS)

Tulsa, OK · Remote

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 ...

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

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

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 ...

micro1 AI

AI Trainer - Microbiology Expert

Tulsa, OK · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Varsity Tutors

Python Tutor

Tulsa, OK · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Stand-By Personnel

Electrical Engineer

Tulsa, OK · On-site +1

$90K - $130K/yr

Remote or On-Site (Tulsa, OK) | Travel Requirement: Up to 25% Employment Type: Direct Hire About ... machine and process controls. You should be able to contribute meaningfully within three months ...

Stand-By Personnel

Electrical Engineer

Tulsa, OK · On-site +1

$90K - $130K/yr

Remote or On-Site (Tulsa, OK) | Travel Requirement: Up to 25% Employment Type: Direct Hire About ... machine and process controls. You should be able to contribute meaningfully within three months ...

Volt Labs Inc.

Senior QA Engineer (Remote)

Tulsa, OK · Remote

$115K - $140K/yr

Senior QA Engineer About Volt At Volt Labs, we're building the infrastructure layer behind modern ... Helping the broader team grow its own AI-enabled QA practices over time we're all learning together ...

Varsity Tutors

Linear Algebra Tutor

Tulsa, OK · Remote

$18 - $40/hr

... data science, engineering, and advanced mathematics. * Conceptual Teaching & Problem-Solving ... machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Mechanical Engineering Tutor

Tulsa, OK · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... transfer, machine design, manufacturing processes, and control systems. Ability to explain free ...

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Remote Machine Learning Engineer information

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$27.3K

$111.6K

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How much do remote machine learning engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for remote machine learning engineer in Tulsa, OK is $111,639.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,000.00 and $134,400.00 per year, depending on experience, location, and employer.

What are some typical challenges faced by remote machine learning engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

What are the key skills and qualifications needed to thrive as a remote machine learning engineer?

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What is a remote machine learning engineer?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

What are the most commonly searched types of Machine Learning Engineer jobs in Tulsa, OK?

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Remote Machine Learning Engineer jobs near you

Machine Learning Engineer (AWS)

CCT

Tulsa, OK • Remote

Full-time

Re-posted 14 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.
 
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.