Machine Learning Engineer Jobs in Dallas, TX
Machine Learning Engineer jobs in Dallas, Texas draw strong demand from technology, financial services, and healthcare employers, with roles concentrating in Uptown, the Platinum Corridor along the North Dallas Tollway, and the Legacy West and Frisco tech corridor. Companies actively 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.
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Find JobsMachine Learning Engineer Job Market in Dallas
Who's Hiring
- GEICO17
- DEPLOY17
- AppFolio17
- JustPark17
- Bain & Company17
Machine Learning Engineer Jobs in Dallas: Frequently Asked Questions
How do I get a machine learning engineer job in Dallas?
Target the sectors hiring most aggressively in Dallas: financial services firms in Uptown and downtown, large health systems and insurers concentrated in the Medical District and Las Colinas, and the technology companies clustered in Legacy West, Frisco, and Addison. Candidates who combine strong Python and cloud platform skills with experience in production ML systems stand out here, since Dallas employers tend to prioritize engineers who can deploy and monitor models, not just build them.
Which companies hire machine learning engineers in Dallas?
Dallas machine learning engineer roles are posted by GEICO, DEPLOY, and AppFolio and others right now, based on current listings on Migrate Mate as of September 2026. The local market includes a mix of Fortune 500 headquarters, regional financial institutions, and mid-size technology companies that have expanded operations into North Dallas suburbs.
Are there remote machine learning engineer jobs in Dallas?
Yes, and machine learning engineering is relatively remote-friendly compared to hands-on technical roles, since most of the work involves code, data pipelines, and model iteration rather than on-site hardware. About 100% of machine learning engineer openings tied to Dallas are remote or hybrid as of September 2026, with fully remote roles most common at software and fintech employers in the North Dallas corridor.
How can I get a machine learning engineer job in Dallas with little or no experience?
The most realistic entry path in Dallas is targeting data analyst or data science roles at mid-size companies in financial services or healthcare, then moving laterally once you have production data experience. Dallas employers such as regional banks, insurance carriers, and health-tech firms regularly hire junior data scientists who demonstrate applied ML project work. A portfolio of deployed models, even personal projects, carries more weight locally than certifications alone.
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