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Senior Machine Learning Ops Engineer Jobs in Dallas, TX

Tiger Analytics

Machine Learning Engineer

Plano, TX · On-site

$120 - $150/hr

Overview Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in ...

WTS Paradigm LLC

Senior Applied ML Engineer

Irving, TX · On-site

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning ... Experience with ML Ops platforms and deploying ML systems into production (MLflow, Kubeflow or ...

Vanguard

Manager, Machine Learning Engineer

Dallas, TX · On-site

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and ... senior technology and business leaders. * Participates in special projects and performs other ...

Paradigm

Senior Applied ML Engineer

Irving, TX · Remote

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning ... Experience with ML Ops platforms and deploying ML systems into production (MLflow, Kubeflow or ...

Crowe LLP

Machine Learning Engineer

Plano, TX · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Crowe LLP

Machine Learning Engineer

Dallas, TX · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

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All JobsMachine Learning Ops Engineer JobsSenior Machine Learning Ops Engineer JobsSenior Machine Learning Ops Engineer Jobs in Dallas, TX

Senior Machine Learning Ops Engineer information

See Dallas, TX salary details

$58.9K

$125.2K

$181.5K

How much do senior machine learning ops engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for senior machine learning ops engineer in Dallas, TX is $125,194.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,400.00 and $142,000.00 per year, depending on experience, location, and employer.

What is a senior machine learning ops engineer?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.

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

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges faced by senior machine learning ops engineers when deploying models to production?

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

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

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

What are popular job titles related to Senior Machine Learning Ops Engineer jobs in Dallas, TX?

For Senior Machine Learning Ops Engineer jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Ops Engineer jobs in Dallas, TX look for?

The top searched job categories for Senior Machine Learning Ops Engineer jobs in Dallas, TX are:

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Cities near Dallas, TX with the most Senior Machine Learning Ops Engineer job openings:

Senior Machine Learning Ops Engineer jobs near you

Graph Machine Learning Engineer (Network)

Vailexa

Plano, TX • On-site, Remote

Full-time

Re-posted 8 days ago

Job description

Build More Than Just a Career. Build Your Future.

At Vailexa, we're not just hiring — we're building thinkers, creators, and future leaders.

We believe in giving people the space to grow, the freedom to think, and the opportunity to create real impact from day one. If you're someone who wants to learn fast, take ownership, and grow beyond limits, you'll feel right at home here.

Summary: We are seeking a talented Graph Machine Learning Engineer to join our team and drive the development of innovative graph-based machine learning models. The ideal candidate will leverage their expertise to solve complex problems and enhance our data-driven decision-making capabilities.

Responsibilities:

  • Design and implement graph neural network models to extract insights from large datasets.
  • Collaborate with cross-functional teams to integrate graph machine learning solutions into existing systems.
  • Develop scalable algorithms for graph data processing and analysis.
  • Perform data pre-processing and feature engineering to ensure high-quality model inputs.
  • Stay up-to-date with the latest trends and advancements in graph machine learning.
  • Conduct experiments to evaluate model performance and refine algorithms as necessary.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
  • Proven experience in machine learning, with a focus on graph-based methods.
  • Strong programming skills in Python and familiarity with libraries such as TensorFlow, PyTorch, or similar.
  • Knowledge of graph databases and query languages (e.g., Neo4j, Cypher).
  • Excellent problem-solving skills and the ability to work independently and collaboratively.
  • Strong communication skills to convey complex technical concepts to non-technical stakeholders.

Ready to take the next step?

If you're excited about this role and ready to grow with a team that values ambition, ideas, and impact — we'd love to hear from you.

???? Apply now and start building your journey with Vailexa.