About the role#
As a Machine Learning Intern at Bland, you will own a focused research project across our voice stack. You will work on 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 solving. We scope projects around a single meaningful question with the goal of producing results worth shipping or publishing. Interns see their work reach production systems that handle millions of calls.
What you'll do#
- Own a research question from literature review through implementation, experimentation, and results.
- Train and evaluate models on large-scale, real-world telephony audio, including noisy and complex speech data.
- Design ablations to isolate what caused a specific improvement.
- Present findings to the research team and defend your methodology.
- Work with engineers to move successful research toward production.
- Focus on areas such as expressive text-to-speech, neural audio codecs, ASR robustness, or real-time streaming inference.
What you'll need#
- Currently pursuing a MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
- Fluency in PyTorch and comfort working in a real codebase.
- Experience with self-supervised, generative, or multimodal modeling.
- Hands-on work with speech or audio models, such as TTS, ASR, or audio representation learning.
- Ability to run experiments on GPU clusters independently.
Location & details#
- Location: San Francisco, California.
- Modality: On-site.
- Employment: Full-time.
- Term: Rolling.
About Bland
Bland builds AI phone agents for enterprise organizations. The company automates customer interactions through voice technology. It is based in San Francisco, California. Founded in 2023, the firm currently employs 135 people.
How to get in at Bland
Applying early at Bland gives you a distinct advantage because recruiters review applications before the pile grows. Intern Insider sends an instant alert the moment a role matching your target is published, so you can be among the first to apply. Securing a spot in the initial batch of candidates keeps your resume at the top of the list. Reaching out to the person behind the role often beats waiting in a queue. Intern Insider surfaces the specific recruiters for Bland, allowing you to contact them directly to ask about the role or a referral. This direct approach materially improves your response rates compared to a standard application.
