About Rhino Federated Computing

Rhino solves one of the biggest challenges in AI: seamlessly connecting siloed data through federated computing. The Rhino Federated Computing Platform (Rhino FCP) serves as the ‘data collaboration tech stack’, extending from providing computing resources to data preparation & discoverability, to model development & monitoring - all in a secure, privacy preserving environment.

To do this, Rhino FCP offers flexible architecture (multi-cloud and on-prem hardware), end-to-end data management workflows (multimodal data, schema definition, harmonization, and visualization), privacy enhancing technologies (e.g., differential privacy), and allows for the secure deployment of custom code & 3rd party applications via persistent data pipelines.

Rhino is trusted by >60 leading organizations worldwide - including 14 of 20 of Newsweek’s ‘Best Smart Hospitals’ and top 20 global biopharma companies - and is leveraging this foundation for financial services, ecommerce, and beyond. The company is headquartered in Boston, with an R&D center in Tel Aviv.

About the role

We are looking for an Applied Data Scientist to join our growing R&D team. You will play a key role in developing the AI capabilities that power our platform, while also acting as a hands-on practitioner who tests and validates our technology across diverse use cases.

In this role, you will balance the immediate needs of a fast-growing startup with long-term data science tasks. You will be responsible for building internal tools that automate complex data workflows, as well as developing and fine-tuning models that demonstrate the full potential of federated computing.

You will work with a wide range of technologies - from integrating off-the-shelf LLM APIs to fine-tuning State-of-the-Art deep learning models - and collaborate closely with Product and Engineering to improve the platform based on your hands-on experience.

Day-to-day responsibilities:

About the candidate

This role is for a fast learner who loves technology and is capable of executing quickly without losing sight of the bigger picture. We are looking for a versatile data scientist who can choose the right tool for the job - whether it’s prompt engineering for an LLM, statistical modeling, or training a deep neural network.

Requirements:

Advantages:

• Experience working in a startup environment.
• Experience with Federated Learning.
• Experience with cloud environments (AWS/GCP) and containerization (Docker/Kubernetes).
• Experience in developing internal developer tools or automation products.