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KOS AI is transforming healthcare with the Argus Continuous Glucose Monitoring System (CGM) – the world’s first non-invasive, optical CGM wristband . Our breakthrough technology uses advanced photoplethysmography (PPG) and machine learning to deliver continuous glucose monitoring without needles, sensors, or patches.
We are building a world-class machine learning team to push the boundaries of AI in healthcare, combining signal processing, multimodal learning, NLP, and deep learning into one platform that changes the way chronic conditions are managed.
Position Overview
We are seeking a Machine Learning Engineer (Entry-Level) with a Master’s in Computer Science (specialized in Machine Learning) and a passion for applying AI across diverse domains. This role is ideal for someone who has a strong academic foundation and exposure to LLMs, NLP, multimodal models, voice recognition, image recognition, and neural networks , and who is eager to learn, contribute, and grow in a fast-paced startup environment.
Key Responsibilities
- Research, experiment with, and implement machine learning models across multiple domains:
- Multimodal models combining text, audio, and image data
- Voice recognition and speech-to-text pipelines
- Image recognition and computer vision architectures
- Neural networks for biosignal and healthcare data
- Develop and optimize end-to-end ML pipelines from training to deployment.
- Work closely with the signal processing and biomedical engineering teams to integrate ML models into real-time embedded healthcare systems .
- Contribute to model evaluation, feature engineering, and dataset curation.
- Stay on top of the latest research in AI, multimodal learning, and medical ML and apply it to real-world use cases.
Required Qualifications
- Master’s degree in Computer Science, Artificial Intelligence, or related field, with specialization in Machine Learning.
- Solid understanding of ML fundamentals, neural networks, and deep learning architectures .
- Exposure to multiple ML domains: NLP, computer vision, multimodal learning, and speech recognition.
- Experience with Python and ML frameworks such as PyTorch, TensorFlow, Hugging Face, or OpenAI APIs .
- Strong problem-solving mindset and ability to work in a collaborative startup environment.
Preferred Qualifications
- Coursework or projects involving healthcare data or biomedical applications .
- Master's Degree in Computer Science and specialization in AI.
- 1-2 years of experience building the elements listed above.
- Familiarity with signal processing or time-series analysis .
- Hands-on experience with transformers, convolutional networks, or multimodal fusion models .
- Publications, Kaggle projects, or research contributions in ML.
Technical Challenges You’ll Solve
- Designing ML models that can handle multimodal data (text, image, audio, biosignals).
- Building lightweight and efficient models for deployment on embedded hardware .
- Adapting cutting-edge AI techniques to achieve clinical-grade accuracy in a real-world healthcare setting.
- Scaling models with diverse and complex datasets across populations.
What We Offer
- Competitive salary and equity package in a high-growth health tech company.
- Opportunity to work on cutting-edge AI projects with real-world healthcare impact .
- Close mentorship from senior ML engineers, biomedical engineers, and researchers.
- Pathway to grow into a specialized ML domain (NLP, multimodal, or biomedical AI).
- A collaborative environment with access to clinical datasets and signal processing experts .
Application Process
Please submit:
- Resume highlighting machine learning projects and academic achievements.
- Cover letter describing your passion for AI and interest in healthcare applications.
- Portfolio of ML projects (GitHub, Kaggle, or research papers).
- Combine everything in one file. Applications with missing elements will be disregarded.
KOS is an equal opportunity employer committed to diversity and inclusion. We welcome applications from all qualified candidates regardless of race, gender, age, religion, sexual orientation, or disability status.
Seniority level
Seniority level
Entry level
Employment type
Employment type
Full-time
Job function
Job function
Engineering and Information Technology
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