Machine Learning Engineer (Up to 30LPA)

Role Overview

Join a VC-backed HealthTech startup to build and productionize ML models that power predictive health insights from radar sensor data. You will work on reliable, real-world ML systems used in production, collaborating closely with hardware, backend, data engineering, and product teams.

Responsibilities

• Build ML models using XGBoost, ensemble methods, anomaly detection, and time-series techniques.
• Develop feature engineering pipelines for radar signals, point-cloud, and sensor data.
• Work on movement, pose, and activity estimation using radar-based data.
• Build training, evaluation, and inference pipelines using Databricks.
• Perform exploratory data analysis to improve model performance and identify edge cases.
• Evaluate models using production metrics such as precision, recall, false alarms, and detection latency.
• Monitor and improve production ML systems across devices and deployments.
• Write clean, production-grade Python code and collaborate with hardware and data engineering teams.

Requirements

• 3–4 years of experience building and deploying ML systems in production.
• Strong Python programming skills.
• Solid understanding of feature engineering, model training, cross-validation, and model evaluation.
• Experience with XGBoost, Random Forests, Gradient Boosting, anomaly detection, or time-series models.
• Good SQL skills with experience using PySpark, Pandas, or Databricks.
• Experience working with sensor, IoT, time-series, point-cloud, or computer vision data.
• Familiarity with Spark, Delta Lake, or modern data engineering workflows.
• Strong debugging, analytical thinking, and ownership mindset.

Nice to Have

• Experience in HealthTech, IoT, or safety-critical systems.
• Exposure to Computer Vision, pose estimation, or object tracking.
• Experience with MLflow, model monitoring, or experiment tracking.
• Knowledge of ONNX, edge deployment, or latency optimization.
• Experience with Kafka, Spark Structured Streaming, or real-time inference systems.

Skills

• Python
• Databricks
• XGBoost
• PySpark
• SQL