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 DEPLOY, Bank OZK, and JustPark. See the openings below and apply to the ones that match your experience.
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The foundation for a great career starts with an exceptional team and a comprehensive benefits package. We believe in providing our dedicated team members with the best resources to support their physical, mental and financial wellbeing, including generous PTO, 401(k) matching, health, dental, vision (and pet!) insurance as well as special perks and discounts. Learn more about Bank OZK benefits.
Job Purpose & Scope:
Essential Job Functions:
- Designs and optimizes prompts for Gen AI and Agentic models/systems, large language models (LLMs) such as GPT, LLaMA, Mistral, and Gemini to achieve business-focused outcomes.
- Develops and maintains retrieval-augmented generation (RAG) pipelines and agentic workflows using tools like LangGraph, AutoGen, Milvus, Pinecone, or Weaviate.
- Builds cloud-native, scalable microservices to support AI applications in production environments.
- Implements AI-powered applications using Python and Java, ensuring robust and maintainable codebases.
- Supports data ingestion, preprocessing, and feature engineering to enable effective model training and deployment.
- Assists in the deployment, monitoring, versioning, and scaling of AI systems on cloud platforms.
- Collaborates with senior engineers, product managers, and research scientists to deliver enterprise-grade AI solutions.
- Monitors advancements in AI/ML research and tools to inform ongoing development and strategic direction.
- Performs other duties as assigned.
Knowledge, Skills & Abilities:
- General knowledge of model fine-tuning and optimization techniques.
- General knowledge of distributed systems and microservices architecture beyond AI applications.
- General knowledge of machine learning fundamentals.
- Strong problem-solving skills and ability to translate business challenges into technical solutions.
- Effective collaboration and communication skills across cross-functional teams.
- Proficient skill with agentic AI orchestration tools such as LangGraph, AutoGen, and Camunda.
- Strong organizational, critical thinking, and time management skills.
- Proficient skill in Python and Java for AI application development.
- Strong skills in LLMs, NLP, and GenAI applications.
- Skill with cloud platforms (e.g. AWS, Azure, GCP) and containerization technologies (e.g. Docker, Kubernetes).
- Skill with databases including SQL, NoSQL, and vector databases.
- Ability to maintain confidentiality and exercise discretion and sound judgment in technical decision-making.
- Ability to work under minimal supervision.
- Ability to manage multiple projects or assignments and demonstrate flexibility in a continually changing environment.
- Ability to build scalable microservices and RAG systems.
Basic Qualifications:
- Bachelor’s degree in Computer Science, AI/ML, Data Science, or a related field, or commensurate work experience required.
- 4+ years of experience in AI/ML engineering or applied AI system development, required.
Job Expectations:
Operate customary equipment and technology used in a business environment, with or without accommodation.
Note: This description is not an exhaustive list of all job functions, duties, skills, and job standards required. Other job functions, duties, skills, and standards may be added. Management reserves the right to add or change the job requirements at any time.
Bank OZK is an equal opportunity employer and gives consideration for employment to qualified applicants without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, disability status, protected veteran status, or any other characteristic protected by federal, state, and local law. Member FDIC.
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Find JobsMachine Learning Engineer Job Market in Dallas
Who's Hiring
- DEPLOY13

- Bank OZK13

- JustPark13

- ServiceNow13

- BlueFlag LLP13B
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 DEPLOY, Bank OZK, and JustPark and others right now, based on current listings on Migrate Mate as of November 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 November 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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