AI ML Engineer

We're building something meaningful — not just another dashboard or data toy. This role is for someone who enjoys working with

real human behavior data

, where every model you ship has the power to improve how people move, live, and take care of themselves.

If you love solving puzzles inside messy, real-world datasets, you'll feel at home here.

What You'll Work On

• Build, train, and refine machine learning and deep learning models using time-series, sensor, and behavioral data.
• Integrate data from wearables, fitness tracking platforms, and device APIs to create a clear story from movement, patterns, and activity signals.
• Develop and maintain data pipelines that support both batch and real-time analytics.
• Own model deployment in production environments — your models won't live in notebooks; they'll live in the world.
• Work closely with engineering teams to integrate ML models into mobile and web apps.
• Support logic for fraud, spoofing, and anomaly detection, ensuring data reflects real human activity.
• Make complex outputs easy to understand — not just for engineers, but for product and business users too.

Requirements

**You'll Thrive Here If You Have**

• 5\+ years of hands-on experience as an ML Engineer or Applied Scientist.
• Strong foundation in machine learning, deep learning, and time-series analysis.
• Experience working with wearables, IoT data, or sensor-based datasets.
• Fluency in Python, PyTorch or TensorFlow, and good software engineering habits.
• Experience building and shipping production ML systems using modern MLOps practices.
• Comfort with Node.js, APIs, and backend integration workflows.
• Understanding of data privacy, cloud ML infrastructure (AWS, GCP, or Azure), and edge inference.
• A solid grasp of feature engineering, statistical reasoning, and evaluating what "good" looks like in a model.

**The Kind of Person We're Looking For**

• You enjoy going deep and figuring things out.
• You care about clarity — in your code, in your thinking, in how you explain your work.
• You see data not just as numbers but as stories about real people.
• You value responsibility. When something is yours, you own it end-to-end