Research Fellow: Reverse Engineering & Vehicle Intelligence Algorithm Development

Company Description

Fleano is pioneering the development of the next-generation AI-native fleet intelligence platform that integrates smart hardware with advanced software. We are committed to revolutionizing transportation through innovative technology, enabling smarter and safer vehicle operations. Our solutions are engineered to address the evolving needs of the fleet industry, creating impactful outcomes for businesses. We value innovation, collaboration, and excellence in every aspect of what we do.

Job description

The role

Own and build algorithms for vehicle health and preventive maintenance by reverse engineering vehicle data, signals, diagnostics, and telematics across Fleano's connected vehicle intelligence platform. This is a Founding Staff role in an early-stage company. Candidates are expected to think and operate like owners this role offers outsized impact, architectural ownership, and long-term upside.

Vehicle Signal Reverse Engineering

• Analyze and interpret vehicle communication protocols including CAN, J1939, OBD-II, and UDS.
• Work with raw vehicle data to identify undocumented signals, decode patterns and behaviors, and build signal mapping strategies.

Algorithm & Intelligence Development

• Convert low-level signals into structured, usable parameters and define derived metrics and relationships between signals.
• Design and implement algorithms for fuel consumption estimation, driver behavior analysis, fault detection, anomaly identification, and vehicle usage and performance patterns.
• Build robust systems that handle noisy or incomplete data, multi-source inputs, and edge-case scenarios.
• Validate outputs using real-world vehicle data and continuously refine models based on field feedback.

What you bring

• 812+ years in automotive systems algorithm development covering predictive maintenance, driver behavior, or fuel systems.
• Strong hands-on experience with CAN bus analysis and vehicle diagnostics including UDS, J1939, and OBD.
• Experience working with real vehicle data, not just simulations or dashboards.

Nice to have

• PhD in Automotive Systems.
• Experience with telematics platforms or fleet management systems.
• Background from automotive OEMs, Tier-1 suppliers, or connected vehicle companies.