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Mlops Jobs in Rosenberg, TX (NOW HIRING)

Bwpmlp

Lead / Sr Analyst Data Scientist

Houston, TX · On-site

$125 - $150/hr

Implement MLOps practices to support scalable, automated model deployment and monitoring. * Ensure compliance with data governance, privacy, and ethical AI standards. * Stay current with industry ...

Eurofins Scientific

Senior Data Engineer

Stafford, TX · On-site

$92K - $125K/yr

MLOps: Familiarity with MLOps platforms and tools such as Azure ML Studio, MLflow, Kubeflow, or Sagemaker. * Chemistry Domain: Basic understanding of analytical chemistry concepts, such as ...

Eurofins

Senior Data Engineer

Stafford, TX · On-site

$92K - $125K/yr

MLOps: Familiarity with MLOps platforms and tools such as Azure ML Studio, MLflow, Kubeflow, or Sagemaker. * Chemistry Domain: Basic understanding of analytical chemistry concepts, such as ...

Koch Industries

AI Architect

Houston, TX · On-site

$60.25 - $79.25/hr

... MLOps practices for model deployment, evaluation, prompt and version management, monitoring, and drift detection • Experience with vector databases and retrieval systems (e.g., Azure AI Search ...

Nam Info Inc

Databricks Azure Consultant

Houston, TX · On-site

$52.50 - $65.25/hr

Knowledge of Machine Learning and MLOps on Databricks. * Experience with streaming technologies such as Kafka and Structured Streaming. * Databricks or Cloud Platform certifications. Qualifications

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Mlops information

What is MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.

What are the key skills and qualifications needed to thrive as an MLOps engineer?

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

Is MLOps in demand?

MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.

Is MLOps outdated?

MLOps is an evolving field focused on deploying and managing machine learning models efficiently. It remains highly relevant as organizations increasingly adopt AI solutions, with skills in automation, cloud platforms, and monitoring tools in demand. Staying current with new tools and best practices is essential for MLOps professionals.

What is the average salary in MLOps?

The average salary for MLOps engineers typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning deployment tend to earn higher salaries.

What cities near Rosenberg, TX are hiring for Mlops jobs?

Cities near Rosenberg, TX with the most Mlops job openings:

Mlops jobs near you
Infographic showing various Mlops job openings in Rosenberg, TX as of August 2026, with employment types broken down into 91% Full Time, 5% Part Time, and 4% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution.

Principal Architect DataBricks

NAVA Software Solutions

Houston, TX • On-site

Full-time

Re-posted 11 days ago

Key responsibilities

  • Design, build, and maintain a library of production-quality reference architectures and reusable patterns for the Databricks platform.

  • Architect and build proofs-of-concept for end-to-end solutions on the Databricks Lakehouse Platform, demonstrating feasibility and validating designs.

  • Create training sessions and lead the adoption of new Databricks features, while providing expert guidance and support to engineering teams.

Job description

NAVA Software solutions is looking for a Principal Architect - DataBricks
Details:
Principal Architect, Databricks
Location: Houston TX - 4 days in office
Duration: Full Time / Direct Hire
The Principal Architect, Databricks will act as our top technical expert and lead practitioner for the Databricks Platform. This role combines architectural leadership with practical implementation. You will be responsible not only for defining the architectural vision but also for developing core, reusable patterns and reference architectures that will accelerate our teams. The ideal candidate is a master of the Databricks ecosystem who leads by example, demonstrates what's possible through hands-on development, and empowers teams to build robust, scalable data solutions.
As a Principal Architect, Databricks you will:
  • Develop and Implement Reference Architectures: Design, build, and maintain a library of production-quality reference architectures and reusable patterns that showcase best practices and accelerate development for engineering teams.
  • Architect and Prototype Solutions: Architect and build proofs-of-concept for end-to-end solutions on the Databricks Lakehouse Platform, actively demonstrating feasibility and validating complex designs through hands-on implementation.
  • Advise Through Doing: Serve as the primary consultant for engineering teams on all aspects of Databricks, providing expert guidance that extends beyond diagrams to include code, best practices, and hands-on support.
  • Lead Platform Training: Create training sessions and train engineers, leading the adoption and implementation of new features such as Unity Catalog, Delta Live Tables, and advanced MLOps capabilities.
  • Establish and Govern Best Practices: Define, document, and evangelize standards for Databricks development, including data modeling, performance tuning, security, and cost management.
  • Mentor and Coach: Mentor engineers and other technical staff through code reviews, paired programming, and design sessions, elevating the overall technical proficiency of the organization within the Databricks ecosystem.

What We Need From You
  • Bachelor's Degree Computer Science or related field. Req
  • 10+ years' Experience in software engineering, including significant experience in architecting systems. Required
  • Proven experience acting as a hands-on technical architect and advisor on large-scale data projects. Required
  • Databricks Mastery: Deep, expert-level knowledge of the Databricks Platform, including: Unity Catalog: Designing and implementing data governance and security. Delta Lake & Delta Live Tables: Architecting and building reliable, scalable data pipelines. Performance & Cost Optimization: Expertise in tuning Spark jobs, optimizing cluster usage, and managing platform costs. MLOps: Strong, practical understanding of the machine learning lifecycle on Databricks using tools like MLflow. Databricks SQL: Knowledge of designing and optimizing analytical workloads. Mosaic AI: Knowledge of designing and optimizing AI Agents.
  • Cloud & Infrastructure: Deep knowledge of cloud architecture and services on AWS. Strong command of Infrastructure as Code (Terraform, YAML).
  • Software Engineering & Programming: Strong background in software engineering and building large fault-tolerant systems.
  • CI/CD & Automation: Experience with designing and implementing CI/CD pipelines (preferably with GitHub Actions) for data and ML workloads.
  • Observability: Familiarity with implementing monitoring, logging, and alerting for data platforms.
  • Automation: The platform is ephemeral, and all changes are implemented using Terraform and Python. Expertise in Terraform and Python is a must.
  • Excellent communication and interpersonal skills, with the ability to influence and guide technical teams and stakeholders effectively.
  • A strategic mindset with a passion for solving complex data challenges and driving business outcomes through technology.
  • The ability to think critically, challenge assumptions, and make clear, well-reasoned architectural decisions.
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About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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