Unlocking your Potential With Data and AI Innovation

In this episode of Technology in Science, host Matthew Witchell speaks with Carlos Peralta, Director of Data Engineering and ML Platforms at WHOOP, to explore how AI in healthcare and data science are redefining personal health tracking. From medical devices to machine learning engineering, WHOOP’s innovations show how technology can help every person better understand their body and unlock long-term potential.

Carlos Peralta, Director at WHOOP

Carlos Peralta is the Director of Data Engineering and Machine Learning Platforms at WHOOP. After nearly a decade at Moderna, where he helped build scalable data systems that powered mRNA vaccine innovation, he joined WHOOP to lead its AI and data engineering strategy. His focus is on building reliable, privacy-first systems that use AI in healthcare to deliver real-time, personalized health insights.

Key Takeaways

• AI in healthcare is enabling predictive, personalized health insights.
• Machine learning engineers are driving innovation in next-generation medical devices.
• WHOOP’s medical tracker gathers member data every 30 seconds for accurate health insights.
• Data privacy, compliance, and model reliability remain top priorities.
• Generative AI in healthcare is unlocking new ways to coach and empower users.

How AI in Healthcare Transforms Everyday Data

WHOOP’s mission is to turn raw biometric data into actionable insight. The company collects heart-rate, recovery, strain, and sleep data from its members almost continuously, generating billions of data points each day. This information fuels an expanding AI healthcare ecosystem that blends machine learning models with behavioral science and human-centered design.

Carlos explains:

 “We collect huge amounts of information from every member, but our mission is to make it digestible, to translate it into something people can actually use to improve their health.”

The WHOOP platform applies advanced AI in medicine to process this data securely and instantly, generating personalized recommendations that support better performance and long-term wellbeing. The result is a medical tracker that functions as a genuine health companion, supporting everything from recovery optimization to sleep and stress management, and expanding into women’s health through smarter, more inclusive data modeling.

From Biotech to AI-Driven Medical Devices

Carlos’s move from Moderna to WHOOP illustrates how healthcare, biotechnology, and consumer technology are merging. At Moderna, his work focused on data systems and AI in medicine, helping develop mRNA vaccine platforms. The environment was highly regulated and precise, centered on software, research, and compliance rather than physical products.

At WHOOP, the challenge shifted to AI in healthcare through a real-world medical tracker that collects data every second from thousands of members. The focus is on turning that information into personalized, actionable insights that improve recovery, sleep, and long-term wellness.

This evolution highlights how AI jobs, machine learning engineer jobs, and AI engineer jobs are expanding across industries. Skills once reserved for biotech are now driving innovation in digital health and connected medical devices, creating new opportunities for professionals who can bridge data science and human health.

Building Trust: Data Privacy and Compliance in Medical Devices

Handling continuous health data requires a foundation of trust. WHOOP integrates medical device compliance and AI security into every stage of its development process.

Carlos emphasizes the need to handle people’s personal data, including their health, habits, and behaviors. 

“Protecting that information is non-negotiable.”

Each machine learning engineer and AI engineer working on WHOOP’s systems is trained to follow privacy-first principles, encryption standards, and global regulations. AI models undergo regular testing and validation to ensure reliability. This disciplined approach reflects the growing demand for AI healthcare professionals who understand both technology and compliance.

Personalized Health Through Machine Learning

No two WHOOP members experience the same health journey. WHOOP’s AI healthcare platform learns from each individual’s data, generating insights based on lifestyle, gender, age, and even environmental factors.

The wearable combines sensor data with journal inputs, creating a detailed picture of recovery, performance, and well-being. Over time, this system evolves into a personalized AI coach that guides members toward smarter habits.

For professionals in machine learning jobs, this represents a defining moment, moving from static algorithms to adaptive systems that understand human variability and drive measurable health improvement.

Generative AI in Healthcare: The WHOOP Coach

WHOOP’s AI Coach, built on generative AI in healthcare, gives users an interactive way to engage with their own data. By partnering with OpenAI, WHOOP created a feature that allows members to ask natural-language questions, such as:

• “How was my recovery last night?”
• “How can I improve my sleep?”
• “Plan a workout based on my recent performance.”

Carlos notes that they wanted to make it easy for anyone to talk to their data. The Coach helps members understand what’s happening in their body and what to do next. This conversational AI experience bridges complex data analysis with practical, human-centered insight, making AI in medicine accessible to everyone.

Expanding the Reach of AI Healthcare

WHOOP is extending its technology beyond fitness into broader aspects of health, including mental health, women’s health, and long-term recovery. Integrations with other medical devices, wearables, and health platforms aim to build a connected digital health ecosystem.

By combining multiple data sources, WHOOP is creating a model of AI in healthcare that is inclusive, ethical, and focused on prevention as much as performance.

The Growing Demand for AI and Machine Learning Jobs

As WHOOP scales globally, it reflects a broader movement in AI healthcare innovation — an increasing need for cross-functional experts who can connect data science with clinical understanding.

Emerging roles include:

• AI engineer jobs in digital health product development
• Machine learning engineer jobs for predictive health modeling
• Data scientist roles focused on healthcare analytics and security

These careers are shaping the future of AI in medicine, proving that the next wave of healthcare innovation will come from interdisciplinary teams that blend engineering, science, and user experience.

The Future of AI in Healthcare: A Human-Centered Vision

Carlos summarizes the company’s philosophy simply:

 “AI is here to make us better, never to replace us. It’s our co-pilot in understanding ourselves and unlocking our potential.”

This mindset captures WHOOP’s mission to keep humans at the center of healthcare innovation. Through continuous learning, responsible AI, and scalable design, WHOOP demonstrates how medical trackers and machine learning engineers can work together to improve daily life, safely and intelligently.

How Barrington James Supports AI and Life-Sciences Growth

At Barrington James, we partner with organizations driving innovation across AI, medical devices, and life sciences. Our consultants connect companies with experts in data science, engineering, regulatory affairs, and clinical development,  helping turn advanced technologies into real-world healthcare solutions.

We support both permanent and contract hiring, sourcing AI engineers, machine learning specialists, and clinical and commercial leaders who can scale innovation safely and effectively.

As a global life sciences recruitment partner, Barrington James helps clients unite technology, science, and patient impact to accelerate progress in AI healthcare and beyond.

Contact our team today.