Senior Data Lead – Autonomous Driving Stack

Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > ADAS R&D Software

General Summary:*

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm ADAS Systems Engineer, you will research, design, develop, and test algorithms that enable autonomous and self-driving vehicles. Qualcomm Engineers collaborate with multiple disciplines across Qualcomm to lead innovation across the industry.

The Senior Data Lead owns the end‑to‑end data strategy and execution for a next‑generation, E2E AI‑based Autonomous Driving stack. The role ensures that data directly enables learning, performance, safety, and scalability across perception & E2E planning using state of art (proven) solutions.

This is a hands‑on technical leadership role, requiring deep experience in AD stack development (ML) and expert‑level understanding of data pipelines, fleet data, training, validation, and closed/open‑loop learning.

Key Responsibilities*

Define and drive the data strategy for an E2E AI / foundation‑model‑based AD stack.

Own the full data lifecycle: fleet ingestion, selection, enrichment, annotation, simulation, reprocessing, and KPIs.

Act as a technical peer to perception, E2E AI, systems, and safety leaders, shaping architecture through data‑driven insight.

Ensure data translates into measurable system and product performance, not just volume.

Enable closed/open‑loop learning from real‑world operation to model improvement.

Align data priorities across core stack, pre‑development, infrastructure, and deployment teams.

Minimum Qualifications:*

Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or related field and 8+ years Software Engineering or related work experience.

OR

Master's degree in Computer Science, Electrical Engineering, Robotics, or related field and 7+ years Software Engineering or related work experience.

OR

PhD in Computer Science, Electrical Engineering, Robotics, or related field and 6+ years Software Engineering or related work experience.

Preferred Qualifications:*

Proven experience in AD/ADAS stack development (perception & planning).

Deep understanding of large‑scale ML / E2E AI systems and how data drives model behaviour.

Strong background in data pipelines, fleet data, MLOps, and validation.

Ability to operate at system and product level, not just data operations.

Principal Duties and Responsibilities:*

• Leverages expert knowledge of ADAS Software to direct and drive the design, development, and optimization of highly complex software for embedded technology blocks that directly enable autonomous and self-driving vehicles.• Develops and implements the technical vision for the enhancement of technologies for camera perception; high precision localization; radar and lidar perception; precise sensor synchronization and calibration; sensor driver; multi-sensor fusion; estimation and tracking of static and dynamic objects in the environment; behavior prediction of agents; planning of autonomous vehicle decisions, trajectory and speed; and/or autonomous vehicle control.• Oversees technical vision for verification; guides multiple teams through verification and validation of design in alignment with product/technology roadmap.• Directs the design and development of software development kits (SDK) to enable customer proof of concepts.• Drives the development of highly complex, efficient techniques to enable data sharing between critical software modules using state of art middleware.• Implements and communicates the guidelines for technical documentation, descriptions, specifications, and/or feature descriptions for projects that guide users and/or customers to use or implement output; writes detailed technical documentation, descriptions, specifications, and/or feature descriptions for highly complex projects.

• Has influence over the formulation and achievement of long-term business plans and objectives.• Tasks often require multiple steps which can be performed in various orders; extensive planning, problem-solving, and prioritization must occur to complete the tasks effectively.