Machine Learning Engineer

We are a tech startup building signal processing solutions on PPG-based physiological data. Our algorithm team designs the core health metric logic - you will be the person who takes that logic and turns it into robust, production-ready code, working closely with both the algorithm team and the app/backend team.

What you will do

• Translate signal processing and health metric algorithms (designed by the algorithm team) into clean, efficient Python/C++ code
• Work with raw and processed PPG signals - preprocessing, filtering, feature extraction, and metric computation
• Integrate algorithms with the app backend - APIs, edge deployment, or real-time pipelines depending on the use case
• Collaborate with the app team to ensure algorithm outputs meet latency, format, and reliability requirements
• Test and validate implementations against expected outputs defined by the algorithm team
• Maintain and version algorithm codebases as logic evolves

What we are looking for

• 1-3 years of hands-on experience in ML engineering or signal processing roles
• Strong Python skills; familiarity with NumPy, SciPy, Pandas, and signal processing libraries
• Comfort reading and implementing algorithms from specs, papers, or pseudocode - you don't need to design them, but you must understand them well enough to implement correctly
• Experience working at the interface of ML/algorithm code and a backend or app layer (REST APIs, real-time data pipelines, or embedded/edge environments)
• Familiarity with physiological signals (PPG, ECG, or similar) is a strong plus
• Good engineering habits - version control, testing, documentation

Good to have

• Experience with on-device or embedded signal processing (Android/iOS SDK, BLE data)
• Familiarity with health wearables or biosensor data pipelines
• Exposure to model optimization for low-resource environments

What this role is not

This is not a research role. You will not be expected to design algorithms from scratch. The right person here is someone who enjoys the craft of clean, reliable implementation and thrives in close collaboration between an algorithm team and an engineering team.

Location: Delhi, hybrid

Compensation: As per industry standards