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Machine Learning Remote Internship Jobs in Texas

Senior Machine Learning Engineer

Austin, TX · On-site +1

$335K - $400K/yr

Willingness to work 4 day in-office, 1 day remote weekly schedule. * PhD or Master's in Computer ... grade machine learning systems, spanning model training, tuning, deployment, serving, and ...

Sr Machine Learning Engineer

Irving, TX · On-site +1

$112K - $185K/yr

Remote work permitted but must live within commuting distance of designated office location and ... Machine learning algorithms; Feature engineering, model training, hyperparameter tuning ...

New

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... The Opportunity The Senior Artificial Intelligence and Machine Learning Engineer will be part of a ...

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Remote-first with co-working access at Industrious offices * 401(k) with employer match * Equity ...

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Remote-first with co-working access at Industrious offices * 401(k) with employer match * Equity ...

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

REMOTE Anticipated Start Date: 07/01/2026 The US base salary range for this full-time position is ... Lead the development and deployment of advanced machine learning models to forecast outcomes and ...

Senior Software Engineer - Remote

Austin, TX · Remote

$121K - $160K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Senior Software Engineer - Remote

Texas City, TX · Remote

$104K - $138K/yr

Remote Job Summary: In this role, you'll apply your expertise to help train next-generation AI ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

... remote within a mutually acceptable location. #LI-Hybrid Success Looks Like: * AI systems move ... Develop and deploy machine learning and generative AI solutions that support enterprise use cases.

Showing results 21-40

Machine Learning Remote Internship information

What is a machine learning remote internship?

A Machine Learning Remote Internship is a temporary, structured work experience where interns contribute to machine learning projects from a remote location, such as their home. Interns typically work with teams on tasks like data preprocessing, building models, and evaluating results, while gaining practical knowledge and mentoring. These internships are ideal for students or recent graduates looking to develop their skills in machine learning, programming, and data science without the need to relocate. They often involve working with Python, popular ML libraries, and real-world datasets. Communication and collaboration are maintained through online tools and regular meetings.

What types of projects can I expect to work on during a machine learning remote internship?

During a remote machine learning internship, you can expect to contribute to projects such as data preprocessing, model development, and performance evaluation. Interns often work on real-world datasets, applying techniques like regression, classification, clustering, or deep learning, depending on the organization's focus. Collaboration with data scientists, engineers, and other interns is common, typically via virtual meetings and shared code repositories. These projects provide hands-on experience and often culminate in presenting your findings to the team, offering valuable exposure to industry-standard workflows and tools.

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

To thrive as a Machine Learning Remote Intern, you need a solid background in programming (especially Python), mathematics/statistics, and a foundational understanding of machine learning concepts, often gained through coursework or relevant projects. Familiarity with machine learning libraries (like TensorFlow, PyTorch, and scikit-learn), version control systems (such as Git), and cloud platforms is typically expected. Strong problem-solving abilities, self-motivation, and effective remote communication set top interns apart. These skills and qualities enable efficient collaboration, successful project delivery, and continuous learning in a dynamic, distributed work environment.

What is the difference between Machine Learning Remote Internship vs Data Science Intern?

AspectMachine Learning Remote InternshipData Science Intern
Required CredentialsBasic programming, math, and machine learning knowledgeStatistics, programming, and data analysis skills
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis and modeling tasks
Industry UsageTech, AI, startups, research labsTech, finance, healthcare, consulting
Search & Comparison IntentUnderstanding internship roles in MLExploring data science internship opportunities

Machine Learning Remote Internships focus on developing models and algorithms, often requiring knowledge of programming and math. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. While both roles are remote and industry-relevant, ML internships emphasize algorithm development, whereas data science roles focus on data analysis and visualization.

What cities in Texas are hiring for Machine Learning Remote Internship jobs?

Cities in Texas with the most Machine Learning Remote Internship job openings:

Infographic showing various Machine Learning Remote Internship 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.

Senior Machine Learning Engineer

Rokt

Austin, TX • On-site, Remote

$335K - $400K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 5 days ago


Job description

Rokt is an ecommerce technology company with the mission of making every transaction more relevant. The Rokt Ecommerce Network leverages proprietary machine learning recommendation systems, powering billions of transactions for hundreds of millions of customers, and is trusted to do this by companies like Live Nation, Fanatics, Macy's, AMC Theatres, PayPal, Uber, Hulu, Staples, Albertsons and HelloFresh.

We are hiring Senior Machine Learning Engineers

We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and product teams to design, build and productionize proprietary machine learning models to solve different business challenges including smart bidding, lookalike modelling, forecasting, etc.

Target total compensation ranges from $335k - $400k, comprised of a fixed annual salary of $210k - $260k, plus employee equity plan grant. In addition, you will receive world-class employee benefits.

Responsibilities

  • Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions for smart bidding, lookalike modelling, forecasting, and related ranking and prediction tasks.
  • Build and productionise machine learning models, including model-specific data pipelines, feature engineering within the team's feature store, and integration with the team's orchestration and serving infrastructure.
  • Evaluate model performance through offline metrics, and monitor deployed models for drift, leading retraining or rollback decisions as needed.
  • Contribute to and maintain the high quality of the code base with tests that provide a high level of functional coverage as well as non-functional aspects such as load testing, unit testing, and integration testing.
  • Keep track of emerging tech and trends, research the state-of-the-art deep learning models, prototype new modelling ideas, and conduct offline and online experiments

Requirements

  • Willingness to work 4 day in-office, 1 day remote weekly schedule.
  • PhD or Master's in Computer Science, Statistics, Mathematics, or related field with specialization in ML, AI, or Information Retrieval (or equivalent experience)
  • Extensive knowledge in and experience with some of the following areas: Bayesian methods, recommender systems, multi-task modelling, meta-learning, click-through rate modelling or conversion rate modelling
  • 3+ years of industry experience building production-grade machine learning systems, spanning model training, tuning, deployment, serving, and monitoring
  • Experience with Kubeflow (or similar), TensorFlow, and a feature store in a production environment is a massive plus
  • Bonus points if you are familiar with any of the following architectures or have experience with the models mentioned: DCNV2, MMOE, Deep & Wide, ESMM, xDeepFM, and GDCN

Benefits

  • Equity in a profitable, fast-growing company approaching $1 Billion in revenue.
  • Dollar-for-dollar 401K matching plan (up to 4% of fixed annual remuneration)
  • Fully funded health insurance (Dental, Optical, and Medical)
  • Generous allowances for wellness, technology, mobile, and transit.
  • Daily catered lunch, stocked pantry & fridges
  • Extra leave (bonus annual leave, sabbatical leave etc.)

Equal employment opportunities are available to all applicants without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

If this sounds like a role you'd enjoy, apply here, and you'll hear from our recruiting team.

Note: The first stage of the recruitment process for this role is to complete a 15-minute online aptitude test, which will be sent out to your application email. Successful candidates will be contacted to discuss the next steps.