Data Engineering team leader

Data Engineering team leader

We are a medical AI startup, aiming to assist the embryo grading task of the in-vitro fertilization (IVF) procedure using deep-learning-based product. We are looking for a senior frontend engineer to join our offshore team and be part of developing our existing and new products. ​​​​

Responsibilities:

 

• Manage the design of our data lake to serve different types of internal and external clients.
• Hands-on development of medical data pipelines, ensuring accurate reception, annotation, and utilization for deep learning purposes 
• Work closely with our deep learning engineers and our clinical researchers
• Work with trained AI models [BK1] as part of automated data pipelines.
• Process huge video and textual datasets of various IVF devices and other medical data sources
• Lead a team of data engineers to design, build, and manage our data infrastructure.
• Collaborate with cross-functional teams such as data science, product, and engineering to develop data-driven solutions.
• Design and implement data pipeline architecture to support our AI products.
• Develop tools and processes to automate data engineering workflows.
• Manage data privacy and regulatory compliance.

 

duh [BK1]

Qualifications

Requirements:

• Bachelor's degree in computer science or a related field.
• 3+ years[BK1]  of experience in data engineering or related roles.
• 3+ years of experience in managerial roles
• A strong vision of data management and accessibility.
• Proven track record of designing and implementing data infrastructure and pipelines for AI products[DT2] 
• Strong coding skills in Python
• Excellent written and communication skills in English

Advantages:

• Experience in HealthTech industry – big advantage
• Familiar with AI and deep learning concepts
• Experience in Airflow[DT3] 
• Experience in K8S
• Experience in MongoDB
• Knowledgeable in image processing

 

the field barely exists for 5 years, better ask for 3 imo [BK1]

we can move the AI part to advantage, we can work with someone that made pipelines for production or other departments [DT2]

familiar with AI and deep learning concepts [DT3]