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Development Ops Engineer Jobs in Dallas, TX (NOW HIRING)

Tiger Analytics Inc.

ML Ops Architect

Dallas, TX · On-site +1

As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers ... Benefits Significant career development opportunities exist as the company grows. The position ...

Whopper Technologies

Front-End Engineer

Dallas, TX · On-site

Experience in dev ops processes and implementation * Deep understanding of performance tuning ... Engineering, and the Public sector. With a focus on deploying top-tier talent and fostering ...

Tiger Analytics Inc.

ML Ops Architect

Dallas, TX · Remote

As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers ... Benefits Significant career development opportunities exist as the company grows. The position ...

Kaav Inc.

Sr. Data Engineer | ONSITE

Dallas, TX

$54.75 - $67.75/hr

... dev ops, product model that includes designing, developing, and implementing large-scale ... engineering solutions • 5-7 years data analytics experience using SQL • 5-7 years of cloud ...

Tiger Analytics Inc.

ML Ops Architect

Dallas, TX

As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers ... Benefits Significant career development opportunities exist as the company grows. The position ...

Kasmo Global

Data Engineer

Dallas, TX

$113K - $136K/yr

... dev ops, product model that includes designing, developing, and implementing large-scale ... engineering solutions. 2. 3+ years of Data Analytics experience using SQL 3. 3+ years full-stack ...

Navtech, Inc.

Sr SAS Developer

Plano, TX · On-site

Optional Skills: • Data Engineering solution delivery using AWS (S3, Glue, Athena, EMR, PySpark, Data lake), Python, Snowflake, Dev Ops and CI/CD tools. • Knowledge and experience working with ...

Jobsbridge

Android Developer

Southlake, TX

$52.50 - $69/hr

... Developer, responsible for developing next generation Entertainment / Account Managing App on ... Experience in Dev OPs, open source, Cloud Technologies. Additional Information Multiple Openings

Jobsbridge

Android Developer

Southlake, TX

$52.50 - $69/hr

... Developer, responsible for developing next generation Entertainment / Account Managing App on ... Experience in Dev OPs, open source, Cloud Technologies. Additional Information Multiple Openings

HiOperator

Senior Software Engineer

Dallas, TX · On-site

Manage dev ops pipeline * Deploy machine learning models * Build and manage the observability platform for the LLMs we utilize You're a great match if you: * Have 5+ years of engineering experience

Xpanxion

SDET

Irving, TX · On-site

$80K - $100K/yr

Qualifications * 5+ years of relevant technical experience. * 5+ years as a software/system tester, integrator, or developer. * 2+ years of experience in Package deployment and dev ops. * 4+ years ...

UST Xpanxion

SDET

Irving, TX · On-site

$80K - $100K/yr

Qualifications * 5+ years of relevant technical experience. * 5+ years as a software/system tester, integrator, or developer. * 2+ years of experience in Package deployment and dev ops. * 4+ years ...

HiOperator

Senior Software Engineer

Dallas, TX · On-site

$120K/yr

Manage dev ops pipeline * Deploy machine learning models * Build and manage the observability platform for the LLMs we utilize You're a great match if you: * Have 5+ years of engineering experience

HiOperator

Senior Software Engineer

Dallas, TX · On-site

$120K/hr

Manage dev ops pipeline * Deploy machine learning models * Build and manage the observability platform for the LLMs we utilize You're a great match if you: * Have 5+ years of engineering experience

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All JobsDevelopment Ops Engineer JobsDevelopment Ops Engineer Jobs in Dallas, TX

Development Ops Engineer information

See Dallas, TX salary details

$48.5K

$95.1K

$151.8K

How much do development ops engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for development ops engineer in Dallas, TX is $95,119.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,600.00 and $105,400.00 per year, depending on experience, location, and employer.

Is DevOps dead due to AI?

DevOps engineers focus on automating and integrating development and operations processes, and AI tools are increasingly used to enhance automation, monitoring, and decision-making. While AI impacts certain tasks, DevOps remains essential for managing complex systems, and the role evolves to include working with AI-driven tools and practices.

What is the difference between Development Ops Engineer vs Software Engineer?

AspectDevelopment Ops EngineerSoftware Engineer
CredentialsTypically requires experience with cloud platforms, scripting, and automation toolsUsually holds a degree in computer science or related field; coding skills essential
Work EnvironmentFocuses on deployment, automation, and infrastructure managementPrimarily involved in designing, coding, and testing software applications
Industry UsageCommon in DevOps teams, tech companies, and organizations emphasizing continuous integrationWidespread across software development, startups, and enterprise IT

While both roles require technical skills and collaboration, Development Ops Engineers focus on deployment, automation, and infrastructure, whereas Software Engineers concentrate on software development and coding. Understanding these differences helps in choosing the right career path or job search focus.

What does a DevOps engineer do?

A DevOps engineer is responsible for automating and streamlining software development, deployment, and infrastructure management processes. They often work with tools like Jenkins, Docker, and Kubernetes to ensure continuous integration and delivery, and they collaborate with development and operations teams to improve system reliability and efficiency.

What is a development operations engineer?

A development operations engineer, often called DevOps engineer, is responsible for combining software development and IT operations to improve deployment frequency, reliability, and automation. They work with tools like CI/CD pipelines, cloud platforms, and scripting to streamline software delivery and maintain system stability.

What engineers make $500,000?

Senior-level engineers in fields such as software development, data engineering, and cloud infrastructure can earn $500,000 or more annually, especially with extensive experience, specialized skills, and stock options or bonuses. Roles in high-demand areas like machine learning, cybersecurity, and DevOps often have higher compensation packages, particularly at large tech companies or startups with significant funding.
What cities near Dallas, TX are hiring for Development Ops Engineer jobs? Cities near Dallas, TX with the most Development Ops Engineer job openings:
Development Ops Engineer jobs near you
ML Ops Architect

ML Ops Architect

Tiger Analytics Inc.

Dallas, TX • On-site, Remote

Full-time

Posted 15 days ago

Job description

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
We are looking for a motivated and passionate Machine Learning Engineers for our team.
Job Description:
As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers that support, build, and enable Machine capabilities across the organization. You will work closely with internal customers and infrastructure teams to build our next generation data science workbench and ML platform and products. You will be able to further expand your knowledge and develop your expertise in modern Machine Learning frameworks, libraries and technologies while working closely with internal stakeholders to understand the evolving business needs. If you have a penchant for creative solutions and enjoy working in a hands-on, collaborative environment, then this role is for you.
Requirements
What you'll do in the role:
  • Implement scalable and reliable systems leveraging cloud-based architectures, technologies and platforms to handle model inference at scale.
  • Deploy and manage machine learning & data pipelines in production environments.
  • Work on containerization and orchestration solutions for model deployment.
  • Participate in fast iteration cycles, adapting to evolving project requirements.
  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
  • Leverage CICD best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
  • Collaborate with Data scientists, software engineers, data engineers, and other stakeholders to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, monitoring, alerting and automated model deployment.
  • Manage and monitor machine learning infrastructure, ensuring high availability and performance.
  • Implement robust monitoring and logging solutions for tracking model performance and system health.
  • Monitor real-time performance of deployed models, analyze performance data, and proactively identify and address performance issues to ensure optimal model performance.
  • Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability in a timely and efficient manner.
  • Implement security best practices for machine learning systems and ensure compliance with data protection and privacy regulations.
  • Collaborate with platform engineers to effectively manage cloud compute resources for ML model deployment, monitoring, and performance optimization.
  • Develop and maintain documentation, standard operating procedures, and guidelines related to MLOps processes, tools, and best practices.

Basic Qualifications:
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
  • Typically requires 7+ years of hands-on work experience developing and applying advanced analytics solutions in a corporate environment with at least 4 years of experience programming with Python.
  • At least 3 years of experience designing and building data-intensive solutions using distributed computing.
  • At least 3 years of experience productionizing, monitoring, and maintaining models

Must have skills:
  • Understanding of Azure stack like Azure Machine Learning, Azure Data Factory, Azure Databricks, Azure Kubernetes Service, Azure Monitor, etc.
  • Demonstrated expertise in building and deploying AI/Machine Learning solutions at scale leveraging cloud such as AWS, Azure, or Google Cloud Platform.
  • Experience in developing and maintaining APIs (e.g.: REST).
  • Experience specifying infrastructure and Infrastructure as a code (e.g.: Ansible, Terraform).
  • Experience in designing, developing & scaling complex data & feature pipelines feeding ML models and evaluating their performance.
  • Ability to work across the full stack and move fluidly between programming languages and MLOps technologies (e.g.: Python, Spark, DataBricks, Github, MLFlow, Airflow).
  • Expertise in Unix Shell scripting and dependency-driven job schedulers.
  • Understanding of security and compliance requirements in ML infrastructure.
  • Experience with visualization technologies (e.g.: RShiny, Streamlit, Python DASH, Tableau, PowerBI).
  • Familiarity with data privacy standards, methodologies, and best practices.

Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

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