Lead Engineer

Responsibilities & Key Deliverables

1. Product Development:
   
   Lead and manage the end-to-end project lifecycle for ADAS system development, from initial concept to full-scale deployment. Ensure timely delivery, adherence to project scope, and meet all technical specifications and quality standards.
   
   Work with cross-functional teams to define system specifications, architecture, and interfaces.
   
   Ensure that product designs are robust and meet all regulatory, safety, and quality requirements.

2. Project Deliverables & Adherence to Processes:
   
   Lead the planning, execution, and tracking of project deliverables to ensure timely completion of milestones.
   
   Take ownership of project timelines, ensuring milestones are met within budget and on time.
   
   Ensure that product development follows established processes and industry standards.
   
   Track and report project status, risks, and mitigations to stakeholders and management.
   
   Develop and execute test cases to validate system functionality, ensuring compliance with safety and performance standards.
   
   Capture and analyze logs from vehicle testing, ensuring that data is accurately interpreted and used to drive improvements.
   
   Work closely with the CFT team to setup End-of-Line (EOL) calibration and verification stations.

3. Quality Maintenance & Process Adherence:
   
   Ensure that the design, development, and testing processes maintain the highest level of quality.
   
   Perform detailed DFMEA (Design Failure Mode and Effects Analysis) to identify and mitigate potential risks early in the design phase.
   
   Define and execute DVP (Design Verification Plan) to validate the system against requirements.

4. Technical Expertise & Development Tools:
   
   Lead the development of ADAS algorithms and system software in programming languages such as C, C++, and Python.
   
   Have hands-on experience with vehicle network architecture, specifically CAN (Controller Area Network) and Ethernet, and manage their integration into the ADAS system.
   
   Use CAN and Ethernet tools for diagnostics, testing, and analysis of vehicle communication.

5. Prototyping & Innovation:
   
   Design, develop, and test prototypes to validate new ADAS features and concepts. Lead the innovation process by introducing new technologies, tools, and methodologies to enhance ADAS solutions. Keep up to date with industry trends and drive forward-thinking solutions.
   
   Be comfortable working in a fast-paced environment that demands flexibility and agility.

6. Mentorship & Team Leadership:
   
   Lead, mentor, guide and grow a high-performing team of engineers, professionally and technically.
   
   Foster a collaborative team environment and promote knowledge sharing to ensure continuous learning, collaboration, and personal development.
   
   Provide leadership in troubleshooting and resolving complex technical issues.

7. Collaboration & Stakeholder Management:
   
   Collaborate with internal and external stakeholders, including suppliers, to ensure product requirements and timelines are met.
   
   Ensure proper documentation and reporting are maintained, including test results, engineering changes, and system specifications.

Experience

9+ years for (M.E/M.Tech)/ 11+ years for (B.E/B.Tech) in automotive systems engineering with a focus on ADAS or related fields, including hands-on experience with system-level engineering, product development, and integration.

Industry Preferred

Automotive

Qualifications

M.E/M.Tech/B.E/B.Tech (Electronics)

General Requirements

Technical Expertise & Development Tools:

Proficiency in development languages such as C, C++, and Python.

Strong understanding of vehicle network architecture, including CAN and Ethernet protocols.

Hands-on experience using CAN and Ethernet tools (e.g., Vector CANalyzer, CANoe, Wireshark).

Expertise in DFMEA, DVP, and testing methodologies.

Proficiency in rapid prototyping techniques. Familiarity with development tools, such as MATLAB, Simulink, or similar tools for simulation and rapid prototyping.

Strong knowledge of ADAS systems, including sensors (cameras, radar, LiDAR), ECU, and algorithms.

Deep knowledge of ADAS technologies, sensor fusion, machine learning, and real-time operating systems (RTOS).

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