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Graduate Machine Learning Engineer Jobs in Texas

... Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Lead Machine Learning Engineer

Houston, TX · On-site

$97K - $128K/yr

Chevron is seeking a Machine Learning Engineer to build and scale production AI solutions that drive critical decisions across subsurface and wells operations. In this role, you will partner with ...

Lead Machine Learning Engineer

Houston, TX · On-site

$97K - $128K/yr

Chevron is seeking a Machine Learning Engineer to build and scale production AI solutions that drive critical decisions across subsurface and wells operations. In this role, you will partner with ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring ...

Lead Machine Learning Engineer

Plano, TX

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale.

Machine Learning Engineer, Senior

Austin, TX · On-site

$103K - $142K/yr

The company is seeking a Senior Machine Learning Engineer to design, train, and maintain models for their counter-sUAS perception stack, focusing on model research and dataset engineering.

HCLTech is looking for an experienced AI/ML Engineer / Data Scientist to design, develop, and deploy advanced machine learning and data science solutions. The ideal candidate will have expertise in ...

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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 Jul 10, 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 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 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 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 July 2026, with employment types broken down into 93% Full Time, 4% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $119,968 per year, or $57.7 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Apple

Austin, TX

$184K - $324K/yr

Full-time

Medical, Dental, Retirement

Posted yesterday


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 667 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

Imagine what you could do here! The people here at Apple don’t just create products - they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work.
Here on the Apple Store Online team, we are responsible for Apple’s largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things.
We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop the next generation of algorithms used to drive the Apple Online experience! The role spans central areas of our Apple Online Store including developing models for product search, recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, messaging, marketing), Generative AI and optimize Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to work on new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers ever day.
Description
To be successful, candidates will need a machine learning background, proven software development skills, a love of learning. They will also need to be able to collaborate with multi-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to help develop and implement machine learning algorithms and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment.
Give to the ongoing improvement of our ML infrastructure and tooling.
Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering.
Mentor junior MLEs on the team to ensure best practices are followed.
Preferred Qualifications
PhD or Graduate degree with research/work experience using data science techniques (including but not limited to Computer Science, Statistics, Mathematics, etc).
Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture.
Skilled in communication, problem solving, critical thinking.
Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plus.
Experience with Spark, TensorFlow, Keras, and PyTorch a plus
Minimum Qualifications
Bachelorʼs degree in Computer Science, Statistics, Mathematics with equivalent experience.
5+ years of related experience building high throughput scalable applications or building machine learning models.
Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems.
Experience building data processing pipelines and large scale machine learning systems with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc.
Skilled in communication, problem solving, critical thinking Attention to detail, data accuracy and quality of output.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

What Apple employees say

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976