Machine Learning Engineer (Up to 30LPA)

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗝𝗼𝗯
This role is for one of our client companies — a VC-backed HealthTech startup that has raised $1M USD in funding.
💰 Salary: Up to 30 LPA
Apply once and, if selected, get access to up to 20 remote and onsite interview opportunities.
🚀 𝗪𝗵𝗮𝘁 𝗪𝗲'𝗿𝗲 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴
CodeRound AI matches the top 5% tech talent with the fastest-growing, VC-funded AI startups across Silicon Valley and India.
Top-tier product startups across the US, UK, EU, UAE, and India have hired exceptional engineers through CodeRound.
🚀 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 (3+ 𝗬𝗲𝗮𝗿𝘀 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲)
We're looking for a Machine Learning Engineer to build and productionize ML models that power predictive health insights from radar sensor data. You'll work on reliable, real-world ML systems used in production, collaborating closely with hardware, backend, data engineering, and product teams.
🧩 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗗𝗼
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 to improve model reliability.
✅ 𝗬𝗼𝘂'𝗿𝗲 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁 𝗜𝗳 𝗬𝗼𝘂
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.
⭐ 𝗚𝗼𝗼𝗱 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.
✨ 𝗪𝗵𝘆 𝗝𝗼𝗶𝗻 𝗨𝘀?
Build AI systems that create meaningful real-world healthcare impact.
Own end-to-end ML solutions from experimentation to production.
Work with cutting-edge radar sensing, IoT, and applied AI technologies.
Collaborate with a high-performing, fast-moving engineering team.
Accelerate your career while solving challenging production ML problems

Work arrangement
Yes