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Machine Learning Remote Internship Jobs in Austin, TX

Kake Group

Senior AI Talent Sourcer

Austin, TX · Remote

Core Requirements * 5+ years of experience sourcing AI , machine learning , LLM , research ... Ability to work independently in a remote, fast-paced environment. Other Traits * Naturally curious ...

HiddenLayer

AI Red Teamer

Austin, TX · On-site +1

Hands-on experience with adversarial machine learning techniques and tools (e.g., Foolbox ... Fully Remote: We are a completely remote global team. Though we're distributed, we are intentional ...

Adidev Technologies Inc

DATA SCIENTIST

Austin, TX · Remote

... Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline Must have * Understanding of various machine learning algorithms (e.g. SVM, Random Forests ...

David Joseph & Company

AI Engineer

Austin, TX · On-site +1

$140K - $200K/yr

Remote (United States) Compensation: $140,000 - $200,000 base Visa Sponsorship: None available ... About the Role As an AI Engineer, you will design, train, and deploy machine learning models and ...

Wsgr

Innovations and AI Solutions Engineer

Austin, TX · On-site +1

This position is available as a hybrid or remote work schedule. Essential Duties, Responsibilities ... Design, build and implement machine learning models, including the development of AI Models and ...

Continued

AI Engineer (Remote)

Austin, TX · Remote

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

continued

AI Engineer (Remote)

Austin, TX · On-site +1

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

Continued

AI Engineer (Remote)

Austin, TX · Remote

Remote Virtual, work-from-home position. Work anywhere in the US, must live in the US ABOUT ... machine learning and generative AI models at enterprise scale. This role will also help define best ...

micro1 AI

Engineering AI Evaluator (PhD)

Austin, TX · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

micro1 AI

Domain Expert - (STEM PhD)

Austin, TX · Remote

$80 - $90/hr

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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Showing results 1-20

All JobsMachine Learning JobsMachine Learning Remote Internship JobsMachine Learning Remote Internship Jobs in Austin, TX

Machine Learning Remote Internship information

See Austin, TX salary details

$25.3K

$42.2K

$87.2K

How much do machine learning remote internship jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning remote internship in Austin, TX is $42,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

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 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 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 are popular job titles related to Machine Learning Remote Internship jobs in Austin, TX? For Machine Learning Remote Internship jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Remote Internship jobs in Austin, TX look for? The top searched job categories for Machine Learning Remote Internship jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Remote Internship jobs? Cities near Austin, TX with the most Machine Learning Remote Internship job openings:
Machine Learning Remote Internship jobs near you

Senior AI Talent Sourcer

Kake Group

Austin, TX • Remote

Contractor

Re-posted 8 days ago

Job description

We're looking for an experienced Senior AI Talent Sourcer to join Kake's internal team and help build exceptional talent pipelines across AI and engineering domains.
In this role, you'll partner closely with recruiters and hiring stakeholders to identify, engage, and attract highly specialized talent, including AI trainers, evaluators, machine learning engineers, research engineers, AI researchers, domain experts, and other specialists contributing to cutting-edge AI initiatives.
If you thrive in complex talent markets, enjoy uncovering hard-to-find candidates, and excel at proactive sourcing strategies, we'd love to hear from you.
What You'll Do
  • Partner with recruiters and hiring stakeholders to understand hiring needs and define sourcing strategies.
  • Own end-to-end sourcing for AI and technical roles, building and maintaining high-quality talent pipelines.
  • Identify, engage, and nurture specialized talent including AI trainers, evaluators, machine learning engineers, research engineers, AI researchers, domain experts, and other specialists contributing to AI model development and evaluation.
  • Leverage a wide range of sourcing channels, including professional networks, technical communities, open-source ecosystems, research platforms, and emerging AI talent networks.
  • Conduct initial candidate assessments and provide insights on talent availability and candidate fit.
  • Maintain accurate candidate data and sourcing activity within the ATS.
  • Contribute to the development of scalable sourcing processes and best practices.

Core Requirements
  • 5+ years of experience sourcing AI, machine learning, LLM, research engineering, or related technical talent, with demonstrated success engaging highly specialized candidates in competitive markets.
  • Experience sourcing for AI training, model evaluation, generative AI, or other AI-focused programs.
  • Strong track record of building talent pipelines through proactive sourcing strategies.
  • Demonstrated ability to identify and engage talent through non-traditional sourcing channels.
  • Expertise in Boolean search, LinkedIn Recruiter, talent mapping, and sourcing research techniques.
  • Ability to assess and differentiate technical backgrounds across software engineering, machine learning, AI research, data science, and related disciplines.
  • Experience sourcing talent globally across multiple geographies, time zones, and talent markets.
  • Strong communication, organizational, and stakeholder management skills.
  • Ability to work independently in a remote, fast-paced environment.

Other Traits
  • Naturally curious and investigative, with a passion for uncovering hard-to-find talent.
  • Proactive, resourceful, and comfortable working independently.
  • Comfortable navigating ambiguity and evolving priorities.
  • Strong collaborator who builds effective partnerships with recruiters and stakeholders.
  • Continuously seeks to improve sourcing strategies, processes, and results.
Additional
  • US Timezone Overlap: 6h–7h daily CST

Please Note: Due to the high volume of applications, only shortlisted candidates will be contacted.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.