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Internship German Machine Learning Jobs (NOW HIRING)

Bland

Machine Learning Intern

San Francisco, CA · On-site

Machine Learning Research Intern, Audio As a Research Intern at Bland, you will own a focused ... We scope internships around a single meaningful question that can be answered in the time you have.

TikTok

$42.75/hr

The team is made up of machine learning researchers and engineers, who support and innovate on ... Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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Internship German Machine Learning information

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

As of Sep 12, 2026, the average yearly pay for internship german machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is an internship German machine learning?

An Internship German Machine Learning is a temporary training position typically offered by companies or research institutions in Germany, focusing on practical experience in machine learning. Interns work on real-world projects involving data analysis, algorithm development, and model implementation under supervision. These internships help students or recent graduates gain hands-on skills, industry exposure, and networking opportunities in the rapidly growing field of artificial intelligence and machine learning.

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

As a German Machine Learning intern, you'll typically assist with real-world projects such as developing and testing machine learning models, preprocessing datasets, and supporting the implementation of AI solutions in both German and international contexts. You may also help with data analysis, model evaluation, and documentation, often collaborating with data scientists and engineers. These projects provide hands-on experience with industry-standard tools and workflows, helping you build practical skills and a strong professional network.

What are the key skills and qualifications needed to thrive as an internship German machine learning?

To thrive as an Internship German Machine Learning, you need a solid understanding of machine learning concepts, programming skills in Python, and progress toward a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, and data analysis libraries, as well as experience using version control systems like Git, is typically required. Strong analytical thinking, problem-solving ability, and effective communication—especially in both English and German—help you collaborate within diverse teams. These skills and qualifications are essential for successfully contributing to machine learning projects and adapting to the fast-evolving tech industry.

What is the difference between Internship German Machine Learning vs Data Scientist German?

AspectInternship German Machine LearningData Scientist German
Required CredentialsBasic programming, coursework in MLAdvanced degree in data science, statistics, or related
Work EnvironmentInternship setting, learning-focusedFull-time, project-driven
Industry UsageEntry-level roles, training programsProfessional roles, decision-making

Internship German Machine Learning positions are typically entry-level, focusing on learning and skill development, often requiring basic programming and coursework. Data Scientist German roles are more advanced, requiring higher education and experience, with responsibilities in analyzing data and building models. The internship provides a stepping stone into the data science field, while the data scientist role involves applying expertise to solve complex problems.

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Internship German Machine Learning jobs near you
Infographic showing various Internship German Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Intern

San Francisco, CA • On-site

Bland
Clean Energy Semiconductors Manufacturing • 51 - 200 employees
Learn more about Blandexternal

Full-time

Posted 15 days ago

Job description

The Role: Machine Learning Research Intern, Audio
As a Research Intern at Bland, you will own a focused research project across our voice stack: speech-to-text, large language models, neural audio codecs, or text-to-speech. You will work alongside our research team on the same problems they are working on, not on a side track built to keep interns busy.
We scope internships around a single meaningful question that can be answered in the time you have. The goal is a result worth shipping, publishing, or both. Interns here regularly see their work reach production systems handling millions of calls.
What You Will Do
Own a research question end to end
  • Take one well-scoped problem from literature review through implementation, experimentation, and results.
  • Design ablations that isolate what actually caused an improvement.
  • Present your findings to the research team and defend the methodology.

Work on real systems
  • Train and evaluate models on large-scale, real-world telephony audio, including the accents, noise, and artifacts that make production speech hard.
  • Use our distributed GPU infrastructure rather than toy-scale setups.
  • Where the result warrants it, work with engineers to move it toward production.

Choose your depth
Depending on your background and interests, your project may focus on:
  • Expressive and controllable text-to-speech, including prosody and emotion modeling
  • Neural audio codecs and discrete or continuous speech representations
  • ASR robustness for telephony, accents, and code switching
  • Real-time and streaming inference under latency constraints
  • Full-duplex conversation and turn-taking dynamics
What Makes You a Great Fit
Research foundations
  • Currently pursuing a MS or PhD in ML, CS, EE, or a related field, or equivalent research experience.
  • Comfortable reading a paper and reimplementing it without hand-holding.
  • Experience with self-supervised, generative, or multimodal modeling.

Audio or speech grounding
  • Hands-on work with speech or audio models, whether TTS, ASR, codecs, or audio representation learning.
  • Strong intuition for audio quality and what makes synthetic speech sound wrong.
  • Prior publications or open source contributions in speech or language AI are a strong signal, though not required.

Engineering ability
  • Fluent in PyTorch and comfortable in a real codebase.
  • Able to run your own experiments on GPU clusters without waiting to be unblocked.
How You Show Up
  • You identify the single experiment that validates an idea in days, not months.
  • You measure everything and let data drive decisions.
  • You are honest about negative results, because they are how we narrow the search.
  • You are obsessed with making voice agents sound truly human.
  • You use AI tools aggressively to amplify your own impact.
Benefits
  • Competitive intern compensation
  • Mentorship from researchers working on frontier voice AI
  • Every tool you need to succeed
  • Beautiful office in Levi's Plaza, SF with rooftop views
  • A real shot at a return offer

Apply