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Machine Learning Research Intern Jobs in Stanford, CA

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 research project across our voice stack: speech-to-text, large language models, neural audio codecs, or ...

New

Samaya AI

ML Research Intern

Mountain View, CA · On-site

Role We are seeking a highly motivated Machine Learning Research Intern to work on cutting-edge research in the fields of Natural Language Processing (NLP) and Machine Learning (ML). At Samaya, our ...

Samaya AI

ML Research Intern

Mountain View, CA · On-site

Role We are seeking a highly motivated Machine Learning Research Intern to work on cutting-edge research in the fields of Natural Language Processing (NLP) and Machine Learning (ML). At Samaya, our ...

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

We apply deep learning research to large scale neural datasets to decode internal thought directly ... You will design and implement advanced machine learning models for EEG-based neural decoding ...

Etched

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

The Machine Learning Research Engineer will propose and conduct novel research to achieve results on Sohu, translating core mathematical operations into performant instruction sequences and ...

Etched

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

The Machine Learning Research Engineer will propose and conduct research to optimize performance on Sohu, collaborating with hardware architects to develop software solutions that leverage the unique ...

Apple

Machine Learning Research Engineer

Cupertino, CA

$150K - $277K/yr

... research practical ML algorithms and build with us the next generation of video technology. We are ... frontier of machine learning - including computer vision, image and video generation ...

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All JobsMachine Learning Research Intern JobsMachine Learning Research Intern Jobs in Stanford, CA

Machine Learning Research Intern information

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How much do machine learning research intern jobs pay per year?

As of Sep 1, 2026, the average yearly pay for machine learning research intern in Stanford, CA is $50,034.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,200.00 and $54,000.00 per year, depending on experience, location, and employer.

What does a machine learning research intern do?

A Machine Learning Research Intern assists in the development, implementation, and evaluation of machine learning models and algorithms under the supervision of experienced researchers. They often preprocess data, run experiments, analyze results, and contribute to research papers or technical reports. Interns also stay up to date with the latest advancements in machine learning, participate in team meetings, and sometimes help in coding or optimizing existing models. This role provides hands-on experience in applying theoretical knowledge to real-world problems and prepares interns for careers in AI research or development.

What are the key skills and qualifications needed to thrive as a machine learning research intern?

To thrive as a Machine Learning Research Intern, you need a strong foundation in mathematics, statistics, programming (especially Python), and an understanding of machine learning algorithms, typically supported by ongoing or completed studies in computer science or related fields. Familiarity with technical tools such as TensorFlow, PyTorch, scikit-learn, and experience with data analysis libraries are commonly required. Curiosity, problem-solving ability, and effective communication skills help interns stand out by enabling them to collaborate, share insights, and adapt to new research challenges. These skills ensure interns can contribute meaningfully to research projects, quickly learn new techniques, and effectively communicate their findings.

What are some typical challenges faced by machine learning research interns during their projects?

Machine Learning Research Interns often encounter challenges such as dealing with limited or messy datasets, tuning complex model architectures, and balancing innovative research with practical implementation. Additionally, they may need to quickly familiarize themselves with unfamiliar frameworks or tools and effectively communicate technical findings to both technical and non-technical team members. Successfully navigating these challenges can provide valuable learning experiences and help interns build strong problem-solving skills for future roles.

What are popular job titles related to Machine Learning Research Intern jobs in Stanford, CA?

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Machine Learning Research Intern jobs near you
Infographic showing various Machine Learning Research Intern job openings in Stanford, CA as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $50,034 per year, or $24.1 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 3 days ago

New

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