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Ai Machine Learning Engineer Jobs in Texas (NOW HIRING)

Lead Machine Learning Engineer

Plano, TX ยท On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... Drive AI Evaluation & Trust: Build and integrate scalable evaluation (Evals) and observability ...

Lead Machine Learning Engineer

Plano, TX

$98K - $130K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... Drive AI Evaluation & Trust: Build and integrate scalable evaluation (Evals) and observability ...

Lead Machine Learning Engineer

Plano, TX ยท On-site

$179 - $205/hr

R249230Lead Machine Learning Engineer**Join the Dealer Tech division within Capital One's Financial ... Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities ...

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Lead Machine Learning Engineer

Plano, TX ยท On-site

$98K - $129K/yr

Lead Machine Learning Engineer Join the Dealer Tech division within Capital One's Financial ... Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities ...

Showing results 41-60

Ai Machine Learning Engineer information

See Texas salary details

$29.3K

$120K

$180.3K

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

As of Sep 4, 2026, the average yearly pay for ai machine learning engineer in Texas is $119,968.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $144,400.00 per year, depending on experience, location, and employer.

What is an AI machine learning engineer?

An AI Machine Learning Engineer is a professional who designs, builds, and deploys artificial intelligence and machine learning models to solve real-world problems. They work with large datasets, select appropriate algorithms, and optimize models for accuracy and efficiency. Their role often involves both software engineering and data science skills, and they collaborate with other teams to integrate these models into products or services. AI Machine Learning Engineers are in high demand across industries such as technology, healthcare, finance, and more.

What are the key skills and qualifications needed to thrive as an AI machine learning engineer?

To thrive as an AI Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python or R), and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow, PyTorch, and scikit-learn, as well as experience with cloud platforms and data processing tools, is highly valued, along with certifications in AI or machine learning. Critical thinking, problem-solving, and effective communication are essential soft skills for collaborating with teams and translating business needs into technical solutions. These competencies are crucial for developing accurate, scalable AI models that deliver real-world value and drive innovation.

What are some common challenges that AI machine learning engineers face when deploying models to production environments?

AI Machine Learning Engineers often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and handling model drift once solutions are live. They also need to collaborate closely with DevOps and software engineering teams to integrate models seamlessly into existing systems, while maintaining performance and security. Addressing these challenges requires a strong understanding of both machine learning principles and software deployment best practices.

What is the difference between Ai Machine Learning Engineer vs Data Scientist?

AspectAi Machine Learning EngineerData Scientist
CredentialsDegree in CS, AI, or related fields; certifications in ML frameworksDegree in CS, Statistics, or related fields; certifications in data analysis
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, where deploying ML models is keyResearch, business intelligence, analytics across industries

While both roles involve working with data and machine learning, Ai Machine Learning Engineers focus on building and deploying scalable ML models in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core focus and responsibilities.

Is AI Machine Learning Engineer in demand?

AI Machine Learning Engineers are in high demand due to the growing adoption of artificial intelligence across industries. They typically require skills in programming, data analysis, and familiarity with tools like TensorFlow or PyTorch, and job opportunities are expected to continue expanding as AI applications become more widespread.

What cities in Texas are hiring for Ai Machine Learning Engineer jobs?

Cities in Texas with the most Ai Machine Learning Engineer job openings:

Infographic showing various Ai Machine Learning Engineer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $119,968 per year, or $57.7 per hour.

Machine Learning Engineer

TeleWorld Solutions Inc

Plano, TX โ€ข On-site

Full-time

Posted 22 days ago


Job description

TeleWorld Solutions is seeking a Machine Learning Engineer for our team! As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior and Lead engineers of the Data Science & Tools Team to analyze Samsungโ€™s deployed network elements. You will utilize skills to query databases to extract data, use skills in Python or R to analyze data such that you can identify 4G/5G network infrastructure and performance issues and build prediction models, ad-hoc tools, and dashboards to communicate your findings with your team and peers.

TeleWorld Solutions is a strategic wireless engineering and consulting firm offering network operators, OEMs and tower companies turnkey design, optimization, network dimensioning and deployment services. 

With the experience of hundreds of thousands of successful implementations, including macro, DAS, Small Cells, and Wi-Fi, the worldโ€™s leading network operators and OEMs trust our knowledge and experience to plan, perform, troubleshoot, and implement an array of technologies and solutions.

Come join our Veteran-Friendly Team. The Company with Great Benefits and certified as "A Great Place to Work".


  • 7+ years of professional experience in Data Science, Data Analytics, and/or Data Engineering with abilities to work with large datasets using demonstrated statistical, predictive modeling and machine learning methods.
  • 3-5 years demonstrated experience on designing, deploying, and maintaining large scale ML systems in a production environment.
  • Work closely with the internal and external stakeholders to explore relationships of 4G/5G KPI measurements and targets (KPI, KQI) for 4G/5G RAN product acceptance and performance monitoring.
  • Collaborate with RF engineers, network engineers, data scientists, platform engineers, product teams, and operations stakeholders to ensure ML outputs are technically accurate, interpretable, and operationally useful.
  • Utilize A/B testing, statistical, and machine learning models to build robust mechanism for product & feature performance analysis, for evaluation of new product & SW releases and 3rd party product evaluation.
  • Aid in product & feature performance analysis, evaluation of new product & SW releases and 3rd party product evaluation using analytics/data science to drive intelligent business decisions.
  • Work with the team to proactively define and interpret data/metrics/KPIs, analyze results, and provide insights to determine operational impact, trends and opportunities for all the 4G/5G RAN products.
  • Prototyping use cases, implementing automations, and developing tools to support and augment manual or repetitive efforts.
  • Communicate key findings to stakeholders using visualizations and/or other suitable methods.
  • Excellent verbal and written communication skills to communicate technical and complex concepts in an easy-to-follow progression.
  • Able to compile analysis output and findings into a succinct story for technical and non-technical audiences.
  • Adapt to changes in a dynamic business environment and, support management initiatives.

  • Graduate Degree in Computer Science, Statistics, Data Science or a related Data Engineering with 7+ years of professional experience is preferred.
  • Programming experience: Python & Spark (preferred) and/or other languages such as R , SQL, Hive, Spark, Javascript, Visual Basic, C++, shell scripting in a linux or IDE environment such as VSCODE, Jupyter, RStudio, etc.
  • Cloud Development Experience โ€“ AWS/Azure/Google utilizing cloud providers such as Databricks or Snowflake
  • Machine learning expertise: GLM Regression (Linear, Logistic, Multinomial), Decision Tree (including Boosted Trees, Random Forest), kMeans/Hierarchical Clustering, Principle Component Analysis, t-SNE, Neural Networks such as transformers and auto-encoders, Bayesian Regression, and Times Series Modeling.
  • Experience using data with high-volume (1TB+) & high-dimensionality (500+ variables per schema), especially within a big data framework (HaDoop, Citus, MongoDB, etc).
  • Experience performing Data Wrangling, Exploratory Data Analysis (EDA), Correlation Analysis, Statistical Methodologies (distributions, hypothesis testing, confidence intervals) & Significance Testing, A/B Testing.
  • Experience with MLOPS concepts and environments such as MLFLOW a plus.
  • Experience with basic linux administration and software development in a linux environment.
  • Experience in hardware resource management and configuration โ€“ CUDA, Docker, KubeFlow, Kubernetes, etc a plus
  • Must possess qualities of being curious and eagerness to learn .
  • Experience with data visualization and ability to quickly grasp statistical methods, and methodologies. Maintain a strong command of current data analytics technology trends, including emerging paradigms and practices.
  • Demonstrated research and problem solving skills via prior work experience. Experience with wireless infrastructure provider and/or operator is desired.
  • Technical knowledge of any wireless technology & procedures including CDMA/EVDO/LTE/Volte and/or 5G a plus.
  • Experience with evaluating service performance trends and proactively defining RAN system performance related issues a plus.
  • Experience of software version control, coding best practices, and use of development management software such as github, bitbucket, etc is desired.
  • Must have a strong work ethic, integrity and work extremely well independently or in a team environment.

Physical/Mental Demands and Working Conditions: The position requires the ability to perform the essential duties and responsibilities in the following environment:

  • Excellent interpersonal and communication skills. Must be skilled in developing and maintaining good working relationships with all appropriate levels within and outside the company.
  • Operate a computer keyboard and view a video display terminal more than 75% of work time in an office work environment

Join Our Veteran-Friendly Team:

Are you a veteran or a veteran spouse with expertise in telecommunications? Join our team at TeleWorld Solutions, where we value your military experience and provide great benefits. We invite all veterans and veteran spouses to bring their skills and dedication to our team.

TeleWorld Solutions is committed to employing a diverse workforce and provides Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law.