ML Engineer Jobs in Dallas, TX
ML Engineer jobs in Dallas are in strong demand, concentrated in Uptown, the Telecom Corridor in Richardson, and the Platinum Corridor along the North Dallas Tollway, across financial services, telecom, healthcare technology, and defense sectors. Employers hiring right now include GEICO, DEPLOY, and AppFolio. See the openings below and apply to the ones that match your experience.
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DEPLOY has been retained by a Dallas, Texas based firm that provides unique SaaS products to automotive dealerships across the United States.
DEPLOY is a Mid Level Machine Learning Engineer for an in office role in Dallas.
DEPLOY's client will hire smart and ambitious doers and set them loose in an exciting and complex technology business where they will build, sell, and deploy call tracking, CRM integration and Artificial Intelligence solutions in a dynamic business environment.
Our solutions attack one of the biggest business problems in existence today: The Phone.
As a member of the Machine Learning (ML) Team you will:
Design & Deploy ML Models:
Develop, fine-tune, and deploy NLP and LLM-driven models using frameworks like PyTorch, TensorFlow, or Hugging Face, ensuring they are robust, scalable, and production-ready.
Build APIs & Pipelines:
Construct APIs and automated pipelines that integrate real-time or batch data (e.g., call transcripts) to power conversational AI features in our products.
MLOps & Model Monitoring:
Implement MLOps best practices—model versioning, automated CI/CD pipelines (Azure), containerization (Docker), orchestration (Kubernetes)—to ensure reliable, repeatable deployments.
Employ infrastructure-as-code (Terraform, AWS CDK) to maintain scalable, cloud-based ML environments on AWS (SageMaker, EC2/Fargate).
Experiment Tracking & Performance:
Track experiments, artifacts, and metrics using MLFlow, Weights & Biases, or ML Studio.
Continuously monitor performance (Prometheus, CloudWatch), troubleshoot issues, and optimize models for latency, accuracy, and scalability.
Cross-Functional Collaboration:
Partner with data engineers, product managers, and senior ML engineers to align technical solutions with business goals.
Contribute to evolving data pipelines and guide improvements based on user feedback and performance metrics. Mentorship & Best Practices:
Participate in code reviews, pair programming, and technical discussions.
Serve as a mentor to junior team members, sharing best practices in ML engineering, MLOps, and model lifecycle management.
Our Ideal Candidates:
3+ years in ML engineering, with hands-on NLP/LLM expertise, ideally deploying transformer-based models (e.g., GPT, BERT) in production.
Strong Python skills and experience with deep learning frameworks (PyTorch/TensorFlow/HuggingFace), plus familiarity with cloud-based ML (AWS SageMaker, EC2), containerization (Docker), and orchestration (Kubernetes).
Working knowledge of CI/CD (Azure), infrastructure-as-code (Terraform/CDK), and experiment tracking (MLFlow, W&B, ML Studio).
A proactive, collaborative approach; eagerness to learn from senior engineers and improve both ML and MLOps skill sets.
Experience with AWS event-driven and streaming architectures (e.g., EventBridge, SQS) to manage large-scale, real-time data handling and ingestion pipelines.
Understanding of security, compliance, and reliability best practices in ML deployments.
Prior work with voice recognition, sentiment analysis, or conversational AI frameworks.
What's in It for You?
Competitive salary package (immediate PTO).
Full benefits package.
Fidelity 401k with company match.
Fun perks including a monthly gym reimbursement, a monthly wellness reimbursement, and a monthly reading allowance.
Weekly catered breakfast, Employee of the Month rewards, regular company events, and bi-weekly happy hours.
Opportunities for continued career growth within the organization.
Fun and collaborative work environment.
DEPLOY has been retained by a Dallas, Texas based firm that provides unique SaaS products to automotive dealerships across the United States.
DEPLOY is a Mid Level Machine Learning Engineer for an in office role in Dallas.
DEPLOY's client will hire smart and ambitious doers and set them loose in an exciting and complex technology business where they will build, sell, and deploy call tracking, CRM integration and Artificial Intelligence solutions in a dynamic business environment.
Our solutions attack one of the biggest business problems in existence today: The Phone.
As a member of the Machine Learning (ML) Team you will:
Design & Deploy ML Models:
Develop, fine-tune, and deploy NLP and LLM-driven models using frameworks like PyTorch, TensorFlow, or Hugging Face, ensuring they are robust, scalable, and production-ready.
Build APIs & Pipelines:
Construct APIs and automated pipelines that integrate real-time or batch data (e.g., call transcripts) to power conversational AI features in our products.
MLOps & Model Monitoring:
Implement MLOps best practices—model versioning, automated CI/CD pipelines (Azure), containerization (Docker), orchestration (Kubernetes)—to ensure reliable, repeatable deployments.
Employ infrastructure-as-code (Terraform, AWS CDK) to maintain scalable, cloud-based ML environments on AWS (SageMaker, EC2/Fargate).
Experiment Tracking & Performance:
Track experiments, artifacts, and metrics using MLFlow, Weights & Biases, or ML Studio.
Continuously monitor performance (Prometheus, CloudWatch), troubleshoot issues, and optimize models for latency, accuracy, and scalability.
Cross-Functional Collaboration:
Partner with data engineers, product managers, and senior ML engineers to align technical solutions with business goals.
Contribute to evolving data pipelines and guide improvements based on user feedback and performance metrics. Mentorship & Best Practices:
Participate in code reviews, pair programming, and technical discussions.
Serve as a mentor to junior team members, sharing best practices in ML engineering, MLOps, and model lifecycle management.
Our Ideal Candidates:
3+ years in ML engineering, with hands-on NLP/LLM expertise, ideally deploying transformer-based models (e.g., GPT, BERT) in production.
Strong Python skills and experience with deep learning frameworks (PyTorch/TensorFlow/HuggingFace), plus familiarity with cloud-based ML (AWS SageMaker, EC2), containerization (Docker), and orchestration (Kubernetes).
Working knowledge of CI/CD (Azure), infrastructure-as-code (Terraform/CDK), and experiment tracking (MLFlow, W&B, ML Studio).
A proactive, collaborative approach; eagerness to learn from senior engineers and improve both ML and MLOps skill sets.
Experience with AWS event-driven and streaming architectures (e.g., EventBridge, SQS) to manage large-scale, real-time data handling and ingestion pipelines.
Understanding of security, compliance, and reliability best practices in ML deployments.
Prior work with voice recognition, sentiment analysis, or conversational AI frameworks.
What's in It for You?
Competitive salary package (immediate PTO).
Full benefits package.
Fidelity 401k with company match.
Fun perks including a monthly gym reimbursement, a monthly wellness reimbursement, and a monthly reading allowance.
Weekly catered breakfast, Employee of the Month rewards, regular company events, and bi-weekly happy hours.
Opportunities for continued career growth within the organization.
Fun and collaborative work environment.
See All 116+ ML Engineer Jobs in Dallas
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Find ML Engineer JobsML Engineer Job Market in Dallas
Who's Hiring
- GEICO17
- DEPLOY17
- AppFolio17
- JustPark17
- Bain & Company17
ML Engineer Jobs in Dallas: Frequently Asked Questions
How do I get a ml engineer job in Dallas?
Focus your search on the financial services firms clustered downtown and along the North Dallas Tollway, the healthcare technology companies concentrated in the Frisco and Plano corridors, and the telecom and defense contractors in Richardson. Candidates who can demonstrate production ML experience, strong Python and cloud platform skills, and familiarity with the regulated data environments common in Dallas industries stand out in this market.
Which companies hire ml engineers in Dallas?
Employers hiring ml engineers in Dallas right now include GEICO, DEPLOY, and AppFolio, based on current listings on Migrate Mate as of September 2026. Dallas attracts a wide range of employer types, from large financial institutions and regional healthcare systems to defense contractors and high-growth technology companies based in the northern suburbs.
Are there remote ml engineer jobs in Dallas?
Yes, ml engineer work is relatively remote-friendly given its desk-based, analytical nature, though roles requiring access to on-premise infrastructure or regulated data environments tend to be on-site. About 100% of ml engineer openings tied to Dallas are remote or hybrid as of September 2026. Model development and research-focused roles in Dallas tend to offer the most remote flexibility, while MLOps and deployment positions more often require in-office presence.
How can I get a ml engineer job in Dallas with little or no experience?
The most realistic entry path in Dallas is targeting associate data scientist or junior ML roles at mid-size fintech companies and healthcare analytics firms in the Plano and Irving corridors, which hire more entry-level talent than the large enterprise employers downtown. Building a portfolio with end-to-end ML projects on cloud platforms common in Dallas industries, such as Azure and AWS, and pursuing internships at regional technology companies or university research programs at UT Dallas gives candidates a concrete local advantage.
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