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Machine Learning Software Engineer Jobs in Dallas, TX

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · Remote

$94.30K - $129.50K/yr

We're more than just a software company -- we're building the cloud and AI-native platform where ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · Remote

$94.30K - $129.50K/yr

We're more than just a software company -- we're building the cloud and AI-native platform where ... Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site +1

$98.10K - $129.20K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Collaborate as part of a cross-functional Agile team to create and enhance software that enables ...

Apex Informatics

Sr. Software Engineer - AI

Irving, TX · On-site

$117.60K - $155.10K/yr

Stay current with emerging technologies and trends in AI, machine learning, and software engineering. Required Qualifications * Bachelor's or Master's degree in Computer Science, Engineering, or ...

Epic

Software Engineer

Frisco, TX · On-site

As a software developer, you will utilize modern methodologies and technologies to innovate and ... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ...

Epic

Software Engineer

Plano, TX · On-site

As a software developer, you will utilize modern methodologies and technologies to innovate and ... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ...

Epic

Software Engineer

Arlington, TX · On-site

As a software developer, you will utilize modern methodologies and technologies to innovate and ... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ...

Trilogy

Senior Software Engineer

Irving, TX · On-site +1

$117.60K - $155.10K/yr

MACHINE LEARNING & AI • Hands-on experience with ML libraries: scikit-learn, XGBoost, LightGBM ... SOFTWARE ENGINEERING FOUNDATIONS • System design -- distributed systems, microservices, event ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

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All JobsMachine Learning Software Engineer JobsMachine Learning Software Engineer Jobs in Dallas, TX

Machine Learning Software Engineer information

See Dallas, TX salary details

$63.1K

$146.6K

$204.2K

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

As of May 30, 2026, the average yearly pay for machine learning software engineer in Dallas, TX is $146,556.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,200.00 and $171,900.00 per year, depending on experience, location, and employer.

What does a Machine Learning Software Engineer do?

A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.

What are the key skills and qualifications needed to thrive in the Machine Learning Software Engineer position, and why are they important?

To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.

What are the day-to-day responsibilities of a Machine Learning Software Engineer?

As a Machine Learning Software Engineer, your daily tasks typically include developing and optimizing machine learning models, collaborating with data scientists and product teams to define requirements, and integrating models into production systems. You’ll work extensively with large datasets to preprocess, analyze, and validate data, as well as monitor model performance and iterate on solutions when needed. It's common to participate in code reviews, contribute to architectural decisions, and maintain documentation for reproducibility and knowledge sharing. This role offers a dynamic and intellectually stimulating environment, making it ideal for those who enjoy solving complex technical problems and working at the intersection of engineering and data science.
More about Machine Learning Software Engineer jobs
What are the most commonly searched types of Machine Learning Software Engineer jobs in Dallas, TX? The most popular types of Machine Learning Software Engineer jobs in Dallas, TX are:
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What cities near Dallas, TX are hiring for Machine Learning Software Engineer jobs? Cities near Dallas, TX with the most Machine Learning Software Engineer job openings:
Machine Learning Software Engineer jobs near you

Machine Learning Ops Lead

Invitus Strategy Solutions LLC

Fort Worth, TX • On-site

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 6 days ago

Job description

Invictus Strategy & Solutions is a Service-Disabled Veteran-Owned Small Business (SDVOSB) providing strategic workforce solutions to mission-critical government and commercial operations. From cleared federal programs to complex industrial projects, we deliver top-tier professionals who drive performance, safety, and results. Our commitment to operational excellence and customer alignment makes us the partner of choice for organizations seeking agile and reliable talent solutions.
Summary
Invictus Strategy & Solutions is seeking a Senior Machine Learning Engineer and MLOps POD Lead to join our growing technical delivery team in Fort Worth, Texas. This on-site role requires strong hands-on experience designing, deploying, and operating production grade machine learning systems integrated with enterprise data platforms.
The selected candidate will lead a small delivery pod of three to five engineers and data scientists responsible for building and operating scalable machine learning pipelines. This role combines hands on MLOps execution with technical leadership, ensuring machine learning systems operate reliably across commercial and government environments with varying regulatory, security, and operational requirements.
This role requires an engineer who remains directly involved in architecture, pipeline design, and production operations while guiding a small team responsible for delivery outcomes.
Key Responsibilities
MLOps Architecture and Execution
  • Design, deploy, and operate end to end machine learning pipelines supporting large scale datasets integrated with enterprise data lakes and data warehouses
  • Build and maintain production grade MLOps systems across cloud platforms including Azure, AWS, and GCP with primary emphasis on Microsoft Azure
  • Implement CI and CD pipelines supporting model training, versioning, deployment, and lifecycle management
  • Utilize MLflow for experiment tracking, model registry management, and model lifecycle governance
  • Monitor model performance, data drift, and system reliability across production environments
  • Ensure machine learning services meet defined reliability and SLA expectations
  • Collaborate with Data Engineering teams to integrate ML pipelines with ETL workflows, feature engineering pipelines, and enterprise data platforms
  • Deploy and manage ML workloads on Kubernetes based environments

Technical Leadership and Delivery
  • Lead a delivery pod of three to five engineers and data scientists responsible for building and operating ML systems
  • Provide technical guidance, mentorship, and code review support to team members
  • Translate business, operational, and regulatory requirements into scalable ML system architectures
  • Own delivery outcomes across commercial and public sector engagements while maintaining quality, security, and compliance requirements

Security, Compliance, and Responsible AI
  • Support machine learning implementations aligned with applicable standards including the NIST AI Risk Management Framework
  • Ensure secure handling of sensitive data including healthcare, bioscience, or government datasets
  • Implement model documentation, bias detection, and mitigation practices across deployed ML systems
  • Support governance and operational oversight for machine learning lifecycle management

Qualifications
  • Bachelor's degree in Computer Science, Data Science, Engineering, or a related discipline, or equivalent professional experience
  • U.S. Citizenship with the ability to obtain and maintain a government security clearance
  • Minimum seven years of experience in machine learning engineering or MLOps supporting production systems
  • Strong proficiency in Python and experience with modern ML frameworks such as PyTorch, TensorFlow, or similar tools
  • Hands on experience designing and deploying machine learning systems in cloud environments including Azure, AWS, or GCP, with demonstrated depth in Microsoft Azure environments
  • Experience implementing CI and CD pipelines for machine learning workflows
  • Hands on experience supporting enterprise data platforms including data lakes, data warehouses, and ETL pipelines
  • Experience deploying or operating workloads on Kubernetes based platforms
  • Strong foundation in software engineering best practices including version control, automated testing, and documentation

Preferred
  • Experience supporting machine learning systems for commercial clients or federal or state government programs
  • Prior technical leadership experience guiding small engineering teams
  • Experience deploying or operating ML systems in regulated cloud environments including Azure Government
  • Familiarity with infrastructure as code tools such as Terraform
  • Experience with AI governance frameworks, model risk management, or ethical AI practices
  • Relevant certifications may include: Microsoft Azure AI Engineer Associate, Microsoft Azure Data Scientist Associate, AWS Certified Machine Learning Specialty, or TensorFlow Developer Certificate

Compensation and Benefits
  • Employer-paid medical, dental, and vision insurance
  • 401(k) with company match
  • Paid time off and holidays
  • Professional development and certification reimbursement

Invictus Strategy & Solutions is unable to provide sponsorship at this time. All applicants must be legally authorized to work in the United States without current or future sponsorship requirements.
EEO Statement
Invictus Strategy & Solutions is an equal opportunity employer. All qualified applicants will receive consideration without regard to any protected characteristic.
The pay range for this role is:
140,000 - 150,000 USD per year (GGI)

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