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Graduate Machine Learning Engineer Jobs in Texas

As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior ... Qualifications Graduate Degree in Computer Science, Statistics, Data Science or a related Data ...

Graduate Degree in Computer Science, Statistics, Data Science or a related Data Engineering with 7+ ... Machine learning expertise: GLM Regression (Linear, Logistic, Multinomial), Decision Tree ...

Machine Learning Engineer

Austin, TX ยท On-site

$100 - $130/hr

Machine Learning Engineer page is loaded## Machine Learning Engineerlocations: Austin, TXtime type: Full timeposted on: Posted Yesterdayjob requisition id: REQ-12438# **As passionate about our people ...

Avride develops autonomous vehicle and delivery robot technology, and they are seeking an experienced Machine Learning Engineer to enhance their autonomous systems. The role involves developing and ...

Machine Learning Engineer Remote with occasional travel to Silver Spring, MD About @Orchard: @Orchard is a growing Woman-Owned Small Business and federal prime contractor delivering mission-critical ...

Machine Learning Engineer

Frisco, TX ยท On-site

$140 - $190/hr

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

Machine Learning Engineer

Addison, TX ยท On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

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Graduate Machine Learning Engineer information

See Texas salary details

$29.3K

$120K

$180.3K

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

As of Aug 19, 2026, the average yearly pay for graduate 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 does a graduate machine learning engineer do?

A Graduate Machine Learning Engineer is an entry-level professional who designs, develops, and tests machine learning models and algorithms. They work with data scientists and engineers to preprocess data, train models, and deploy solutions to solve real-world problems. Their responsibilities often include coding in languages like Python, using libraries such as TensorFlow or PyTorch, and staying updated with the latest advancements in machine learning. This role serves as a starting point for a career in AI, providing hands-on experience in building and optimizing intelligent systems.

What are some common challenges faced by graduate machine learning engineers during their first year, and how can they overcome them?

Graduate Machine Learning Engineers often encounter challenges such as bridging the gap between academic knowledge and real-world application, working with large or messy datasets, and learning to collaborate within cross-functional teams. Adapting to production-level code standards and understanding existing codebases can also be demanding. To overcome these hurdles, it's helpful to seek mentorship from experienced colleagues, actively participate in code reviews, and invest time in learning best practices for data preprocessing and model deployment. Embracing continuous learning and open communication will ease the transition into the professional environment.

What are the key skills and qualifications needed to thrive as a graduate machine learning engineer, and why are they important?

To thrive as a Graduate Machine Learning Engineer, you need a solid foundation in computer science, mathematics (especially statistics and linear algebra), and proficiency in programming languages like Python, often supported by a relevant degree. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and experience with cloud platforms or data management tools are typically expected. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate and translate complex concepts into practical solutions. These skills and qualities are crucial for developing robust models, integrating them into real-world applications, and contributing effectively to multidisciplinary teams.

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

AspectGraduate Machine Learning EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related field; some internshipsBachelor's or Master's in Statistics, Data Science, or related field; often with experience
Work EnvironmentDeveloping ML models, coding, testing algorithmsAnalyzing data, creating visualizations, deriving insights
Employer & Industry UsageTech companies, startups, research labsFinance, healthcare, tech, consulting firms

While both roles involve working with data and algorithms, Graduate Machine Learning Engineers focus on developing and deploying machine learning models, often requiring coding and technical skills. Data Scientists analyze data to extract insights and inform decisions. The roles overlap in skills but differ in primary responsibilities and focus areas.

Infographic showing various Graduate Machine Learning Engineer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% 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 8 days ago


Job description

Overview

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 Samsung'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.ย 

With the experience of hundreds of thousands of successful implementations, including macro, DAS, Small Cells, and Wi-Fi, the world'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".

Responsibilities
  • 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.
Qualifications
  • 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 - 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 - 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.

Employment Type: FULL_TIME