Principal Engineer

Qualcomm•San Diego, CA

2d•Onsite

About The Position

Auto AI Systems: Team Lead We are seeking a highly qualified AI Systems Team Lead who will be responsible for overseeing a team of machine learning engineers in the design and implementation of state-of-the-art Visual Language Action Models (VLAs), VLMs, LLMs used for low-level perception (LLP), end-to-end autonomous driving and infotainment applications with a focus on achieving accuracy-latency Pareto optimality. The team will be tasked with designing state-of-the-art Low-Level Perception systems as well as end-to-end AD design and deployment on the Qualcomm Ride platform for L2/L3 ADAS/Autonomous driving. Additionally, the team will be responsible for enhancing the speed, accuracy, power consumption, and latency of deep networks operating on Snapdragon Ride AI accelerators. The ideal candidate must be well-versed in recent advancements in VLAs, VLMs, LLMs and Vision Transformers (Cross Attention, Self-Attention), lifting 2D features to BEV space, and their applications to multi-modal fusion. The role requires facilitating collaboration with various Qualcomm horizontal AI teams. Furthermore, the candidate will be responsible for engaging with advanced R&D teams of leading Automotive OEMs as well as Qualcomm's internal stack teams. A strong knowledge of machine learning algorithms, particularly those related to automotive use-cases (autonomous driving, vision, and lidar processing ML algorithms), is essential. Research experience in the development of efficient networks, network quantization is highly desirable. Good exposure to deploying networks in resource constrained devices is desired for this role. The candidate will also be responsible for building a team of world-class AI/deep learning engineers.

Requirements

Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Systems Engineering or related work experience.
Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Systems Engineering or related work experience.
PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience.
Works in the lab, can use hazardous chemicals (e.g., glue, machinery).

Nice To Haves

PhD in related field with 5+ years of relevant experience, master’s with 10+ years, or Bachelor of engineering with 12+ years of relevant experience.
Previous experience in leading ML engineers.
Strong interest towards team leadership, cross functional collaboration and mentoring/guiding new team members.
Strong understanding of Machine Learning fundamentals with multiple external publications/patents.
Hands-on experience with deep learning network design and implementation.
Good at software development with excellent analytical, development, and problem-solving skills.
Experience in deep learning kernel/compiler optimization.
Strong communication and interpersonal skills are required

Responsibilities

Serves as a technical expert in identifying patterns of issues in systems-level software and hardware design and implications for work across teams; provides support to multiple teams to address issues and generate solutions; creates well-defined architectures that meet ambiguous requirements and/or have a financial impact.
Advises multiple teams in design reviews to facilitate platform development; drives evaluation of total system performance based on constraints and/or capabilities to support design integrity.
Takes ambiguous requirements, business requirements, and aligns cross-functional efforts to ensure internal and/or external customer requirements are gathered and agreed upon; communicates a technical vision for guiding multiple teams to design products and solutions.
Acts as a technical lead and owns complete testing for software and hardware performance and quality; supports multiple teams through testing, data analytics, and validation of design; defines specifications for software and hardware; works with leaders to guide architectural decisions related to multimedia systems-level software, hardware, and/or products.
Ensures appropriate tools are being used and supported across multiple teams; acts as an expert in identifying patterns of issues and implications for work; supports multiple teams to address issues.
Serves as a technical expert when leading teams by translating strategic goals and roadmaps into smaller projects and desired features; uses deep and broad technical understanding to review the team's new algorithms, provide implications for work across teams, and triage complex technical issues by generating new solutions and involving others; decide how solutions would be partitioned on the SOC level.
Serves as a technical expert and provides support to teams on data engineering or data management issues for machine learning solutions within a domain.
Acts as a technical lead for teams developing machine learning solutions; reviews and helps write proposals or roadmaps for complex products; consults with staff engineers to ensure they understand development requirements for products.
Provides technical expertise to others within the team regarding experiments to train and evaluate machine learning solutions and communicates progress to key stakeholders.
Evaluates topologies against performance, and cost variables and uses the feasibility findings to review the high-level design for multiple products, product families, or technologies; provides guidance, direction, and decision making; presents the analysis and the recommended route/topology that should be used to maximize performance, quality, and costs while reducing risks to the schedule and implementation.
Acts as a technical expert to others on industry trends, competitors' products, and advances in various engineering fields related to multimedia systems products and technology; reviews technical articles and publications; shares solutions and seeks best practices from open-source community; shares expertise within and/or across teams.
Leverages deep technical expertise to identify trends and define future solutions by contributing to discussions on the short- and long-term strategic direction of the product/technology roadmaps.
Leads technical conversations; resolves cross functional design and technical issues related to technical area of expertise; sets expectations and is an example for teams in documenting technical and/or overall system issues; participates in patent application reviews.