Formal position title: Machine Learning Research Graduate Intern (NLP, ASR)
Job Overview: Intron is a health-tech startup building ASR for clinicians with African accents, helping reduce burnout from tedious documentation for already overworked doctors across Africa. Clinical Speech Recognition is ubiquitous in developed countries but virtually absent across Africa or underperforms with African accents. You can help fix that! Through the contributions of over a thousand African clinicians, we have created Africa’s largest and most diverse clinical speech datasets (10,000+ hours, 300+ accents). Come put your superpowers to work doing ASR, TTS, Clinical NER, Machine Translation, and Generative AI!
Learn more about our work:
- Recent Research: https://www.intron.io/research/
- BBC News Interviews: https://www.bbc.
com/news/av/world-africa- 66033811 - Zindi Challenge by Intron, Huggingface & NVIDIA: https://zindi.africa/
competitions/intron- afrispeech-200-automatic- speech-recognition-challenge - TechCabal article: https://techcabal.
com/2023/05/29/intron-health- brings-ai-to-african- healthcare/ - ASR Masterclass by Intron x NVIDIA x Huggingface: https://www.
intron.io/nvidia-x-intron- nemo-masterclass/ - Product demo: https://youtu.be/
ZV10YNUNGYY
Employment type: Remote (Part-time or Full-time) for 3-6 months. Up to $2,000 per mo, based on the number of hours available per week, experience, qualifications, and cultural fit.
Who You Are:
- Completing a graduate degree in Computer Science
- Fluent with Python
- Machine learning and deep learning research/experience are required. Nice to have: experience should go beyond basic fine-tuning, inference, and API calls to explore making architectural or algorithmic modifications to models, loss functions, optimizers, etc.
- Understand the math and core concepts that underly deep learning, e.g. gradient descent, momentum, regularization, overfitting, bias-variance, etc
- Research, projects, or publications in Natural Language Processing and/or Automatic Speech Recognition are required.
- Experience working with deep learning frameworks (Pytorch, Tensorflow, etc.) and related tools.
- Experience with conversational agents, text generation, or summarization is a plus but not required
- Distributed training with multiple GPUs in the cloud (AWS/GCP/Azure)
- Understands the theory and practice of the Design of Experiments and statistical analysis of results.
- Comfort collecting, manipulating, combining, and analyzing complex, high-volume, unstructured data from varying sources.
- Familiar with the techniques and limitations of observational studies.
- Publication record in top ML/DL conferences/workshops is a plus but not required.
We are looking for people who are:
Growth-oriented: Strong desire to push your ideas into production, overcoming obstacles, ready to learn, and grow your skills to match any challenge.
Personable and Fun: You are great to work and talk with
User-focused: You are passionate about deploying models and applications that improve the lives of millions of users and enjoy research that has direct user impact.
Communicative and collaborative: You are able to work effectively with others. You will be working closely with other researchers, engineers, designers, product managers, user experience researchers, and customer groups to build product features and high-quality products.
Nimble: Balancing short-term execution with longer-term concerns, can pivot when necessary
Ownership: You have demonstrated feature development ownership, and can take initiative and responsibility for building, shipping, and maintaining core features, end to end.
How to apply: Please fill out the application form and upload your resume by clicking the “Apply” button below. Your resume should be in reverse chronological order showing your most recent experience/projects first. Under each experience, kindly provide 3 to 4 bullet points describing interesting problems you solved, achievements, or important lessons learned on the job. The Education/Academic qualification section should follow. Next, the achievements/awards section could follow. Lastly, include any other information you think may be RELEVANT to the role.
Check out our Intron Careers page for more roles.
Learn more about our mission at Intron.