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Machine Learning Research Intern Jobs (NOW HIRING)

Samaya AI

ML Research Intern

Mountain View, CA

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 ...

Roboflow

Machine Learning Research Engineer

The Machine Learning Research Engineer will develop novel methods and contribute to the research agenda, helping to translate innovative research into production systems that effectively address user ...

Roboflow

Machine Learning Research Engineer

The Machine Learning Research Engineer will develop novel methods and contribute to the research agenda, helping to translate innovative research into production systems that effectively address user ...

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

As of Aug 26, 2026, the average yearly pay for machine learning research intern 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 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.
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Machine Learning Research Intern jobs near you
Infographic showing various Machine Learning Research Intern job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Research Intern 2027

Phonic

San Francisco, CA • On-site

Full-time

Re-posted 11 days ago

Job description

About Phonic
Phonic is a product and research lab focused on powering the most realistic, human-like voice AI conversations. We've re-thought the entire stack in pursuit of this goal, from models to product, to create voice agents that feel like they truly understand you, respond emotionally and perform agentic tasks with frontier intelligence.
Our team includes top-tier AI researchers, international olympiad medalists, and former founders.
Our customers include companies that are building voice-native AI products in industries such as customer support, healthcare, and logistics. We have raised over $30M from tier 1 VCs.
About the Team
Phonic has a very talent-dense and close-knit team. We collaborate with high trust and are constantly trying to improve how we work to deliver world-class research and product. Everyone takes ownership in what they do and they aren't afraid to dive in headfirst into new problems. Our team includes top-tier AI researchers, international olympiad medalists, and former founders and we're fully in-person in our SF office.
The Role
As a Research Intern at Phonic, you'll work directly on the core problems that make Phonic's voice AI feel genuinely human. You'll own a research direction end-to-end - from identifying the right problem to designing experiments, developing novel methods, and seeing results through to production impact. This isn't a role focused on incremental improvements; we're looking for someone with the taste to identify what matters, the rigor to pursue it correctly, and the drive to ship it. You'll be fully in-person in our SF office.
What You'll Do
  • Identify high-leverage research problems across the voice AI stack from audio understanding to audio output, and take full ownership of driving them forward
  • Design and run rigorous experiments that analyze architectural trade-offs to understand how design choices influence a model's scalability, latency, and quality
  • Curate massive training datasets and execute rigorous experiments to determine exactly how data quality shapes model behavior and performance
  • Work directly with research scientists and engineers to move fast from prototype to production
  • Build the training pipelines, evaluation frameworks, and tooling that let us experiment and iterate quickly
What You'll Bring
  • A track record of original work: you've found a real problem, developed an approach, and seen it through
  • Proficiency in PyTorch (or JAX), and the ability to implement models cleanly from papers
  • Fluency in the math, probability, optimization, and linear algebra underlying model behavior
  • You move fluidly between ideas and implementation; you don't just think about problems, you build things
  • Clear, precise written and verbal communication
Nice To Have
  • Research experience in speech, audio, or language modeling (ASR, TTS, LLMs, codec models)
  • Familiarity with generative modeling techniques: diffusion, flow matching, or autoregressive models
  • Experience with RLHF or preference optimization
  • Competitive programming or olympiad background
  • Publications or preprints at venues like NeurIPS, ICML, ICLR, Interspeech, ICASSP, or ACL

Benefits
  • Top-tier compensation: in order to get the best talent, we provide salary and equity that recognize your skillset
  • Meals: free breakfast, lunch, and dinner provided in the office
  • We have regular off-sites and team celebrations

Apply