Data/ML Engineer

Inside the data-engineering team you will be in charge of evoling our current infrastructure while working closely with the data-science team who is in charge the medical and research aspects.

Who we are

We are an innovative and dynamic health tech startup focused on providing tech-enabled integrated care for patients with heart failure.

We believe that by implementing cutting edge heart science on top of a modern data platform we can create revolutionary solutions that improve healthcare outcomes.

What we are building

At the forefront of health tech innovation, we improve the lives of patients with Heart Failure

We are developing a Software as a Medical Device (SaMD) platform, tailored to enhance care for patients with heart disease by delivering crucial insights.

Our data platform, hosted on AWS cloud, seamlessly ingests real-time data from a variety of wearable devices. Utilizing state-of-the-art Data Science and Machine Learning techniques, we analyze and compute key metrics and insights that are essential tools for informed decision-making by healthcare professionals.

The results generated by our data pipeline are translated into user-friendly dashboards, web applications, and mobile apps, providing access for patients, physicians, and caregivers.

Our Engineering Vision

We are a small distributed engineering team building the Prolaio platform on AWS.

We are proud of our software that is built on robust foundations:

  • Modular and evolutive architecture
  • Clean code
  • Comprehensive automation: from Continuous Integration, Infrastructure as Code, to continuous deployments
  • Baked-In observability and compliance

If you are passionate about healthcare and thrive in a fast-paced, team-oriented environment, we’d love to hear from you!

What We Offer

  • A collaborative and supportive work environment fueled by science
  • Flexible working hours and competitive benefits package
  • The opportunity to make a real impact on the healthcare industry

Job Description

At Prolaio, our SaMD (Software as Medical Device) relies on a robust data pipeline to transform patient data into actionable insights. If you're a passionate engineer with a keen interest in healthcare, you could play a critical role in enhancing our system and working alongside our data scientists.

Our current pipeline contains multiple steps:

  • Parsing / cleaning
  • Computing new metrics
  • Reviewing metrics & QA

and leverage mulitple technologies

  • Databases / Time Series / Data Lake
  • SQL / Pandas / PySpark
  • AI & ML

Inside the data-engineering team you will be in charge of evolving our current infrastructure while working closely with the data-science team who is in charge the medical and research aspects.

Key Responsibilities

Optimize our Data/ML Pipeline

  • Collaborate closely with our product and data science teams to refine and expand our existing data processing system in AWS
  • Contribute to the different applications used for reviewing/enhancing our medical data (such as Label Studio)
  • Design, implement, and maintain our ML platform using all the latest Machine Learning Operations (MLOps) tooling in AWS

Support our Data Science Team

  • Think of our data scientists as your customers, ensuring they get the best tools to do their jobs.
  • Provide the engineering tools and processes they need to experiment and iterate on models efficiently.
  • Help the data science team to push their work into production with performance analysis and code reviews.

Maintain and Monitor the System

  • Ensure every addition to the data pipeline is backed by thorough automated testing.
  • Design, implement, and maintain the CI of Prolaio Platform (with GitHub actions, AWS CodePipeline)
  • Monitor system health and performance using DataDog.

Required Qualification

  • Strong problem-solving skills, attention to details, and an analytical mind.
  • Proficient in Python / Pandas and ideally also PySpark.
  • Solid understanding of Machine Learning and AI concepts.
  • Hands-on experience of AWS, Docker and associated technologies.

Bonus points

  • Prior collaboration with data scientists and researchers
  • Experience with MLOps tools such as Metaflow and AWS SageMaker
  • Experience with AWS CDK, Code Pipeline, and GitHub Actions
  • Prior experience in the healthcare industry