ADAS Architect –

- Vehicle Dynamics &
- Ego-Motion Estimation

About The Team

You will join a focused team of domain experts building a greenfield, in-house L2+ ADAS software stack for Indian road conditions, covering four-wheelers and two-wheelers. The team designs and owns the complete architecture, algorithms, and tooling, from first principles through to deployment on automotive-grade ECUs. Engineers here shape foundational technical decisions, work directly with experts across perception, fusion, driving functions, motion control, and simulation, and see their work carried from concept to vehicle.

Role purpose The Vehicle Dynamics Architect leads the design and development of the ego-motion estimation component, which provides the host vehicle's speed, acceleration, yaw rate, side-slip angle, and curvature to motion control, driving functions, and sensor fusion. The role is responsible for the accuracy, latency, and integrity of these signals across four-wheeler and two-wheeler platforms.

Key Responsibilities

- Define the architecture and interfaces of the ego-motion estimation component, including published accuracy and latency specifications for all consumers.
- Design and implement state estimation from IMU, wheel speeds, steering angle, and vehicle bus signals, using Kalman-filter, observer, or factor-graph methods selected by analysis.
- Estimate longitudinal and lateral velocity and acceleration, yaw rate, side-slip angle, and path curvature, with consistent uncertainty estimates.
- Develop online calibration of gyroscope and accelerometer biases, IMU mounting misalignment, effective wheel radius, and steering-angle offset.
- Implement signal plausibility checks, sensor-fault detection, and graceful degradation.
- Develop ego-motion estimation for two-wheelers, including lean-angle estimation and its effect on inertial measurements.
- Agree and verify interface requirements with Motion Planning &
- Controls, Driving Functions, and Sensor Fusion.




- Validate estimation performance in simulation with realistic sensor error models, through resimulation of recorded drives, and against reference measurement equipment.
- Implement deterministic, real-time C++ for target ECUs within defined memory and cycle-time budgets.
- Contribute to safety analysis in line with ISO 26262.
- Author technical proposals and the long-term roadmap for vehicle dynamics and ego-motion estimation across subsystems.
- Provide technical guidance, design reviews, and mentoring to engineers working on vehicle dynamics.

Required Qualifications

- Bachelor's or Master's degree (PhD a plus) in Mechanical/Mechatronics, Electrical/Electronics, Control Engineering, Robotics, or a related discipline.
- 7-15 years of experience in vehicle state estimation, ego-motion, odometry, or inertial navigation.
- Demonstrated development of estimators deployed in production or pre-production vehicles.
- Strong foundation in estimation theory: Kalman-filter family, observability, filter consistency and tuning, bias estimation, and handling of delayed and asynchronous measurements.
- Solid knowledge of vehicle dynamics: bicycle model, tyre slip and friction, longitudinal/lateral coupling, and effects of road grade and bank.
- Practical knowledge of MEMS IMU error characteristics, wheel-speed sensing, steering sensors, and CAN signal timing.
- Proficiency in C++ (C++14/17) for embedded, real-time systems, and in Python for analysis
- MATLAB/Simulink is an advantage.
- Working understanding of vehicle motion control and of how estimation errors affect closed-loop performance.

Preferred Qualifications

- Experience with ADAS SoCs (e.g., TI Jacinto/TDA, Renesas R-Car, or equivalent)



and their debugging and profiling tools.
- Experience owning an ego-motion or vehicle-dynamics module consumed by multiple ADAS functions.
- Experience validating estimators against reference equipment (e.g., high-grade INS/GNSS).
- Experience with two-wheeler dynamics or lean-angle estimation.
- Patents or publications in vehicle state estimation or sensor calibration.
- Experience using AI-assisted software development tools in an engineering workflow.

Key competencies

- Ability to explain complex trade-offs clearly to engineers and leadership to drive technical decisions.
- First-principles problem solving and the ability to justify design decisions with data.
- Strong attention to signal integrity and systematic error detection.
- Ownership of work from concept to vehicle, without reliance on handoffs.
- Comfort building current systems where architecture and processes are still being defined.
- Clear technical communication with cross-functional teams (motion control, driving functions, fusion, and test).

L&T; Company Overview / About Us L&T; is a USD 30 billion Indian multinational engaged in EPC Projects, Hi-Tech Manufacturing, and Services, operating across multiple geographies. A strong, customer–focussed approach and the constant quest for top-class quality have enabled L&T; to attain and sustain leadership in its major lines of business for eight decades. Given L&T;’s capability in strategic electronics and leveraging its foray into semiconductor design and well-established capabilities in L&T; Technology Services, the business is expanding its offerings to cover industrial electronic modules, products and systems in critical sectors of Power Electronics, Automotive Electronics, Industrial Robotics &

- Automation, Communication Platforms and Electronic Systems Design &
- Manufacturing (ESDM). The focus products under Automotive Electronics are ADAS, Electrification &
- Connectivity related products.

📌 ADAS Architect - Vehicle Dynamics & Ego-Motion Estimation (Bengaluru)
🏢 Larsen u0026 Toubro
📍 Bengaluru