Build the Future of Vehicle Health

Vehicle Health Algorithm Engineer

Engineering

About Raste

Raste is a predictive vehicle health platform for everyday drivers. We process supported vehicle data to understand mechanical health and identify developing concerns across systems such as the engine, transmission, brakes, wheels, tires, battery, and cooling system.

Raste acts as a vehicle health companion that monitors performance during normal driving and explains what may need attention. This gives drivers a clearer understanding of the vehicles they own, helping them plan maintenance earlier and avoid the inconvenience and anxiety of a sudden breakdown.

Role Overview

We are seeking a Vehicle Health Algorithm Engineer to join our team on a contract basis. While our primary vehicle health prediction models (including cooling, clutch slip, tire wear, and engine life) are currently active in production, we need an engineer to lead the next phase of development: refining predictive accuracy, reducing sensor noise, and ensuring model robustness.

In this role, you will have end-to-end ownership of the algorithmic lifecycle — from physical-domain research and signal processing design, to writing production Python code, to orchestrating deployments on cloud infrastructure.

Key Responsibilities

  • Algorithm Development & Refinement: Lead and improve core vehicle diagnostic modules (including Engine Health, Cooling System, Transmission/Clutch Slip, and Brake/Tire Wear).
  • Signal Processing & Noise Mitigation: Design filters and processing pipelines to turn noisy, high-frequency OBD sensor telemetry (RPM, speed, throttle position, coolant temperatures) into stable, physics-grounded health metrics and alerts.
  • Production Engineering & Data Architecture: Write clean, production-grade Python code. Implement dual-storage patterns (migrating and synchronizing vehicle state summaries across Google Cloud Storage CSV logs and Google Firestore snapshots).
  • End-to-End Ownership: Run research, build Python modules, package containers via Docker, and deploy worker revisions.
  • Mathematical Parity: Maintain mathematical and logical alignment across core prediction models, ensuring consistent analytical calculations across our iOS, Android, Windows and macOS dashboards.

What We Are Looking For

  • Education: B.Tech or B.Sc in Mechanical, Aerospace, Electrical, Computer Science, ECE, or a related technical field.
  • Experience: Minimum 1–2 years of professional experience in algorithm design, vehicle diagnostics, or high-frequency sensor signal processing.
  • Core Technical Stack: Strong proficiency in Python (specifically pandas, numpy, and scipy) along with Google Cloud Platform services (Cloud Run, Cloud Storage, Firestore).
  • Physical Systems Knowledge: A strong understanding of physical systems, automotive mechanics, or aerospace dynamics. You should be comfortable translating mechanical laws and thermal dynamics into software constraints.
  • Relevant Project Background (experience in one or more of the following):
    • Predictive maintenance in automotive, industrial IoT, or aerospace.
    • Structural health monitoring or vibration analysis.
    • Numerical physics modeling or weather prediction.
    • Wearable biometric algorithms (e.g., HRV, VO2 max, sleep staging).

Technical Pluses (Nice to Have)

  • Familiarity with OBD-II protocols and Classic Bluetooth RFCOMM SPP communication.
  • Experience with statistical filtering (e.g., Coefficient of Variation ratios, moving-median baselines, piecewise score interpolation, Arrhenius rate equations).
  • Experience with standard containerization (Docker) and serverless deployment workflows.

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