Vehicle Health Algorithm Engineer (Remote)

About Raste

Raste is an AI-powered vehicle diagnostics platform that predicts mechanical failures before they happen. We log and process actual system sensor data to understand mechanical health and the probability of breakdown in systems like the engine, transmission, brakes, wheels & tires, battery, etc. This has huge applications in the corporate vehicle fleet industry, which spends over $300 billion annually on vehicle maintenance. Over 40% of this maintenance is unplanned, leading to heavy downtime expenses on top of massive repair bills that could have been resolved for far less if detected at the right time. 

With in-depth, data-backed knowledge of the vehicle, Raste acts like a personal AI Engineer that constantly monitors performance and flags degradation weeks in advance. This gives drivers and fleet owners a clear understanding of the vehicles they own, helping them spend less on repairs and actively schedule their maintenance rather than reacting when a breakdown occurs.

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.

• Signal Processing & Noise Mitigation: Design filters and processing pipelines to turn noisy, high-frequency sensor data into stable, physics-grounded health metrics and alerts.

• Production Engineering & Data Architecture: Write clean, production-grade Python code. Implement dual-storage patterns.

• End-to-End Ownership: Run research, build Python modules, package containers, 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 Fo r

• 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.

Job Details

• Workplace Type: Remote
• Employee Location: India (Delhi preferred) or San Francisco
• Job Type: Contract
• Company: Raste Inc.