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We are looking for a motivated and enthusiastic Data Science Student to support our AI and data management efforts. The role involves data collection and preparation, Deep Learning models architecture design, implementation, training, and evaluating algorithm results mainly in the medical imaging domain. Additionally, you will help with other data-related tasks as needed to support our operations. What you will be doing : Data Collection: Gather, organize and prepare (including augmentation) data from various storage locations using tools such as Excel and Python scripting. Develop python code for automatic data collection. Deep Learning Models – Implementation and Training: Analyze to decide what kind of model to use, implement it, train it and adapt to improve the model results. Evaluate Model Results: Visually and empirically assess AI model and other computer vision algorithms outputs, providing feedback and scoring to improve model performance. Assist in Other Data Related Tasks: Organize data from different sources, clean it and implement automatic data collection and preparation pipeline scripts. · Working according to Insightec Quality Policy, relevant Quality Procedures & Standards, and privacy & safety rules.

We are looking for a motivated and enthusiastic Data Science Student to support our AI and data management efforts. The role involves data collection and preparation, Deep Learning models architecture design, implementation, training, and evaluating algorithm results mainly in the medical imaging domain. Additionally, you will help with other data-related tasks as needed to support our operations.
What you will be doing :
Data Collection: Gather, organize and prepare (including augmentation) data from various storage locations using tools such as Excel and Python scripting. Develop python code for automatic data collection.
Deep Learning Models - Implementation and Training: Analyze to decide what kind of model to use, implement it, train it and adapt to improve the model results.
Evaluate Model Results: Visually and empirically assess AI model and other computer vision algorithms outputs, providing feedback and scoring to improve model performance.
Assist in Other Data Related Tasks: Organize data from different sources, clean it and implement automatic data collection and preparation pipeline scripts.
Working according to our Quality Policy, relevant Quality Procedures & Standards, and privacy & safety rules.

We are looking for a Senior backend engineer who is strong in Python and enjoys building reliable, data-intensive systems. You will help develop our next-generation platform, integrations with external data sources, and the services that collect, process, and expose data throughout our product.
This is primarily a backend engineering role - not a pure data engineering or DevOps position. However, you should be comfortable working with data pipelines and taking services through the full lifecycle, from design and implementation to production monitoring.
This is a hybrid position, including two work-from-home days per week, with flexibility .
Responsibilities
Design, build, and maintain backend services using Python and FastAPI.
Develop reliable integrations with external APIs, platforms, and data providers.
Build and improve data-collection and processing workflows, including scheduled, asynchronous, and long-running workloads.
Contribute to our new platform and capabilities such as algorithm execution and data collection orchestration.
Design efficient data models and queries for operational databases and analytical systems such as Amazon Redshift.
Handle real-world integration challenges including rate limits, retries, partial failures, idempotency, and changing external schemas.
Improve the performance, scalability, observability, and reliability of existing services.
Own features end to end: technical design, implementation, testing, deployment, monitoring, and ongoing improvement.
Collaborate with product and engineering colleagues to turn ambiguous requirements into pragmatic technical solutions.

We are on a mission to redefine how consumers go from noticing a need to buying the right solution online. In an internet shaped by AI, fragmented attention, and constantly shifting platforms, we build, own, and scale top-performing brands and offers - both our own and those of leading partners - by combining proprietary technology, data -driven decision making, and creative excellence at performance scale. We operate at consumer scale, reaching millions of people every day across paid channels, owned funnels, and digital touchpoints. In a world where creative trends, consumer behavior, and platform algorithms shift overnight, we stay ahead of the curve. We move fast, think deeply, and build with purpose. Our culture is rooted in entrepreneurship, innovation, and collaboration - along with shared wins, team dinners, and a whole lot of good food and laughter. Were a team of doers, and boundary-breakers - product, data, R&D, growth, and creative talent who own the Full Stack of how consumer brands are built and scaled today. After 17 years in the game, every funnel, every TEST, every brand decision happens in-house - which means your work moves the needle directly and visibly. If youre ready to tackle meaningful challenges, grow at lightning speed, and help shape the next frontier of consumer brand building, you belong here.?About the role We are looking for a Senior backend engineer who is strong in Python and enjoys building reliable, data -intensive systems. You will help develop our next-generation platform, integrations with external data sources, and the services that collect, process, and expose data throughout our product. This is primarily a backend engineering role-not a pure data engineering or DevOps position. However, you should be comfortable working with data pipelines and taking services through the full lifecycle, from design and implementation to production monitoring. This is a hybrid position, including two work-from-home days per week, with flexibility.
Responsibilities:

* Design, build, and maintain backend services using Python and FastAPI
* Develop reliable integrations with external APIs, platforms, and data providers.
* Build and improve data -collection and processing workflows, including scheduled, asynchronous, and long-running workloads.
* Contribute to our new platform and capabilities such as algorithm execution and data collection orchestration.
* Design efficient data models and queries for operational databases and analytical systems such as Amazon Redshift.
* Handle real-world integration challenges including rate limits, retries, partial failures, idempotency, and changing external schemas.
* Improve the performance, scalability, observability, and reliability of existing services.
* Own features end to end: technical design, implementation, testing, deployment, monitoring, and ongoing improvement.
* Collaborate with product and engineering colleagues to turn ambiguous requirements into pragmatic technical solutions.

Biz Dev:
R&D
Remote/Part time:
Hybrid

You will play a key role in ensuring our customers successfully deploy, integrate, and operate our platform. By leading complex technical integrations and solving challenging infrastructure problems, you'll directly impact customer success, platform reliability, and the delivery of critical healthcare data solutions.

What You'll Do
Own end-to-end integrations for large enterprise customers.
Work with modern cloud technologies across AWS, Azure, and GCP.
Solve unique technical challenges involving infrastructure, security, networking, and automation.
Collaborate closely with Engineering, Product, Customer Success, and customer technical teams.
Influence architecture, best practices, and the future direction of our deployment and integration processes.
Lead customer onboarding and technical integration projects from planning through production deployment.
Design, deploy, and troubleshoot cloud infrastructure using Infrastructure as Code (Terraform, Ansible, CloudFormation).
Implement and support Kubernetes, compute, networking, storage, and security configurations across multiple cloud providers.
Automate deployment, upgrade, and operational workflows to improve reliability and efficiency.
Investigate and resolve complex production issues, performing root cause analysis and driving permanent fixes.
Partner with customers and internal engineering teams to deliver scalable, secure, and highly available solutions.
Develop technical documentation, implementation guides, and operational runbooks.
Mentor engineers and contribute to improving engineering standards, tooling, and operational excellence.