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Senior Machine Learning Ops Engineer Jobs in Houston, TX

Socket.dev

Robotics Machine Learning Engineer

Houston, TX · On-site

$120 - $180/hr

We're looking for a Machine Learning Engineer to drive our machine learning strategy. We are primarily interested in candidates who have developed and released products to market, but can be flexible ...

Bespoke Labs

Machine Learning Engineer

Houston, TX · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Oxy

Advisor IT Systems - AI/ML Ops

Houston, TX

We are seeking a midcareer MLOps / AI Ops Engineer to support the deployment, monitoring, and lifecycle management of machine learning and advanced analytics solutions across upstream Oil & Gas ...

Oxy

Advisor IT Systems - AI/ML Ops

Houston, TX · On-site

We are seeking a mid-career MLOps / AI Ops Engineer to support the deployment, monitoring, and lifecycle management of machine learning and advanced analytics solutions across upstream Oil & Gas ...

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

Senior Machine Learning Ops Engineer information

See Houston, TX salary details

$56.8K

$120.9K

$175.2K

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

As of Aug 15, 2026, the average yearly pay for senior machine learning ops engineer in Houston, TX is $120,858.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $137,000.00 per year, depending on experience, location, and employer.

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 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 most commonly searched types of Machine Learning Ops Engineer jobs in Houston, TX?

The most popular types of Machine Learning Ops Engineer jobs in Houston, TX are:

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

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

Senior Machine Learning Ops Engineer jobs near you

Machine Learning Intern, Manipulation

Persona AI

Houston, TX • On-site

Full-time

Posted 14 days ago

Job description

Job Title: Machine Learning Internship, Manipulation
Department: Robotics Software Engineering
Employment Type: Internship, Fall 2026 (August - December) or Spring 2027 (January - May)
FLSA: Exempt
Location: Houston, TX - Onsite
Who We Are
Persona AI is developing and commercializing rugged, multi-purpose humanoid robots that perform real work. Persona AI's founding team has a decades-long history in humanoid robotics, bionics, and product development delivering robust hardware that has touched the stars, worked miles below the surface of the ocean, and even roamed Disney Parks. Our mission is focused squarely on shipping beautiful, reliable products at massive scale, while building a customer-focused team to achieve these aims.
About the Role
We're looking for a Machine Learning Intern (Manipulation) to help build Persona's machine learning models and infrastructure. We are primarily interested in candidates with experience and relevant projects in robot learning, but can be flexible depending on aptitude and energy.
As a Machine Learning Intern at Persona, you will have an incredible opportunity to work with humanoid robots and solve practical problems in the real world.
What You'll Do
  • Work with the ML team to develop and improve machine learning models and the infrastructure.
  • Monitor and evaluate the performance of models in the real world.
  • Collaborate on the design and development of the Persona ML software stack and support its application in manipulation, navigation, locomotion, and perception.

What We're Looking For
  • Courage and grit to tackle some of the hardest problems in embodied AI.
  • Enthusiasm for working collaboratively in a high paced team environment.
  • Experience with deep learning frameworks (Pytorch, JAX, TensorFlow, etc.)
  • Experience with cloud computing to develop models, manage data, etc. (AWS, Azure, GCP)
  • Strong understanding of the state of the art research in robot learning (behavior cloning and reinforcement learning for manipulation, world models, etc.).
  • Understanding of the challenges of deploying neural network models in the real world.
  • Capable of writing high-quality software.
  • Thrive in fast-paced and ambiguous environments.
  • Strong first principles thinker.

Preferred or Bonus Qualifications
  • An advanced degree (Master's or PhD) in computer science, robotics, machine learning, or another related field.
  • Published papers at top ML/Robotics conferences (ICML, ICRA, CoRL, RSS, NeurIPS).

Persona AI is an Equal Opportunity Employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law.

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