Data Science Internship

sonio; France; On-site; EUR 10,000 - 13,000; Full time

Job summary

Sonio is seeking a DS/ML Engineer intern to join its Data Science team, bridging R&D, ML engineering and product. You will work on developing of our Deep Learning/Computer Vision pipelines using state-of-the-art algorithms.

Responsibilities include understanding fetal ultrasound anatomy, training detection/segmentation models, and integrating results into our AWS/SageMaker/MLflow infrastructure. Strong ML/DL knowledge and Python are required; English is essential, French is a plus.

Qualifications

• Currently pursuing Master 2 / Bac+5 in CS/DS, 5–6 month internship.
• Strong knowledge of ML/DL algorithms and Python.
• Experience with PyTorch/HuggingFace and CV tasks.
• Fluent in English; French is a plus.

Responsibilities

• Develop clinical understanding of fetal ultrasound in the anatomical areas you will work on.
• Explore and train different approaches for Detection and Segmentation of anatomical structures and views, and integrate results in ML infrastructure (AWS, SageMaker, MLflow).
• Explore the possibility of training Foundation Models for Ultrasound Imaging.
• Run evaluation protocols and document experiments; publication possible if results support it.

Skills

Machine learning

Deep learning

Python

PyTorch/HuggingFace

Computer vision

English proficiency

French (optional)

Education

Master 2 / Bac+5 in Engineering or related (CS/DS)

Tools

AWS

SageMaker

MLflow

Job description

About Sonio

Each year, 140M children are born. Birth defects affect 1 in 33 births in developed countries, and in 50% of cases, they are not detected during prenatal examinations. Prenatal medicine is particularly complex, and the scans impose heavy responsibilities on healthcare professionals. They can also be a source of stress for future parents.

Resulting from 5 years of collaboration between world-renowned experts from Necker Hospital and Ecole Polytechnique, Sonio uses artificial intelligence to improve prenatal screening and diagnosis. Based on patented algorithms and a proprietary expert database, Sonio aims to become the reference tool to help practitioners improve screening, reduce diagnostic errors, and optimize pregnant women's medical path.

Sonio's mission is to improve women's and children's health by promoting access and quality of care through technological innovation, medical expertise, and collective intelligence.

About the role

We are looking for a DS/ML Engineer intern to join our Data Science team. Your mission will at the crossing of R&D, ML Engineering and product, supervised by senior ML engineers. You will work on developing of our existing Deep Learning/Computer Vision pipelines using State-of-the-art algorithms.

Responsibilities

• Develop clinical understanding of fetal ultrasound in the anatomical areas you will work on,
• Explore and train different approaches for Detection and Segmentation of anatomical structures and views, and integrate your results in our ML infrastructure (AWS, SageMaker, MLflow),
• Explore the possibility of training Foundation Models for Ultrasound Imaging,
• Run evaluation protocols consistent with the way our models are evaluated during regulatory submissions, and document your experiments so the team can build on them. Publication is possible and encouraged if the results support it.

About the profile

Sonio is a mission-driven company so interest in our mission is critical.

• Currently in Master 2 / Bac+5 of Engineering School or University, you are majoring in Computer Science or Data Science and are looking for an internship lasting between 5 and 6 months,
• Good knowledge of Machine Learning and Deep Learning algorithms, and the willingness to explore and work on state-of-the-art algorithms,
• Solid Python and PyTorch/HuggingFace, and comfortable with segmentation and detection architectures,
• Strong interest in computer vision and women's health. A first experience with medical images is a plus,
• You speak English and ideally French.

We move fast and aspire to be transparent over the process - our objective is that the process from the first chat to an offer is no longer than a month. We also aspire to give an answer to every application in a week.