General Summary:

Qualcomm is a global leader in connected intelligent edge, focusing on AI, edge computing and connectivity. Our fast‑growing Industrial and Embedded IoT (IE‑IoT) BU leads the transformation of industries through intelligent edge solutions that combine connectivity, compute, and AI. We expand our global talent in applied edge AI to support our customers’digital transformation across many verticals and industries.

In this position you willbe involvedand participate in building best-in-class solutions and tools needed to enable state-of-the-art technologies for next generation mobile/embedded machine learning platforms for robotics,IOT devicesand datacenter In this role, you will work in a dynamic environment, be part of a multi-disciplinary team, collaborate with internal teams, work with popular neural network frameworks, and understand the architecture of Qualcomm’s SOC and ML HW accelerators. You willsupportapplications usingmachine learning tools and frameworks that enable making models smaller and run efficiently on all edge devices.

Minimum Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Applications Engineering, Software Development experience, or related work experience.
  OR
  Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Applications Engineering, Software Development experience, or related work experience.

• Strong communication and interpersonal skills, high motivation, the ability to learn quickly and must be a self-starter.

• 2+ years of work experience with Programming Language such as C, C++, Python, etc.

• Experiencewith embedded systems - exposure to one or more of Linux, Yocto, Ubuntu based systems.

• Proficiencyindeep learning and machine learning frameworks like TensorFlow, TFLite, PyTorch,Onnxand deployment‑oriented inference workflows.

• 1+ year of any combination of academic and/or work experience with device debugging techniques.

• Ability to speak fluent Portuguese and English

• Excellent communication skills (verbal, presentation, written).  

Preferred Qualifications

• Experience with software engineering foundations (Python/C++), containerization, AI accelerators, and profiling tools; coupled with fluency in modern inference/runtime stacks.

• Knowledge of machine learning, deep learning, quantization, and optimization.

• Experience with different Neural Network architectures: DNNs, CNNs, RNNs/LSTMs, GANs, LLMs, etc.

• Have knowledge in on-device AI models deployment is a plus.

• Experience using/integrating Qualcomm AI Stack products (e.g. QNN, SNPE, QAIRT)is a plus

• Background with Qualcomm AI platforms and heterogenous acceleration; familiarity with on‑device inference and memory/power budgeting.

• Skills in neural network programming, video/image processing, and application development.

• Proficiencyinmachine learning data pipelines, data management, and both backend and frontend applications.

• Theoretical knowledgeofhybrid AIdesigns placing workloads across device/edge/cloud; knowledge of data pipelines, streaming/vision services, vector/RAG stores, feature stores, and observability.

• Experience withsystem‑level understanding of IoT, embedded systems, Edge AI deploymentsandAI On-Premsolution

• Background in computer vision, video analytics, or edge AI inference.

• Experience delivering customer‑facing IoT or Edge AI solutions that moved beyond PoC to pilot or production.

• Experience with multimedia frameworks (Android, Linux, any other OS).  Gstreamer experience a plus.

Principal Duties and Responsibilities

• Support deployment of computer vision and generative AI models (e.g., LLMs and vision-language models) onQualcommplatforms(IoT, Datacenter), helping customers move from development to commercialization.

• Support pre-sales and post-sales customer engagements as a solution engineer, translating business requirements into technical solutions, optimizing AI workloads, providing deployment guidance, and driving issue investigation and resolution.

• Translate customer requirements, use cases, and business needs into technical solutions leveraging Qualcomm AI engines (AI accelerators) and SoCs.

• Provide internal enablement (training, documentation, and hands-on support) and help resolve technical issues as they arise.

• Collaborate cross-functionally with internal teams and external partners (OEMs, ISVs, system integrators, and cloud providers) to align requirements and validate end-to-end solutions.

• Improve tools, workflows and documentation by identifying gaps, implementing enhancements, and measuring impact.

• Assist in developing and integrating generative AI (including LLM) features intoQualcomm platformsapplications.

• Perform machine learning model benchmarking (both accuracy and latency) and functional analysis meet customer KPIs

• Act as a technical lead for customer engagements, supporting projects from discovery throughsolution selection,PoC, pilot, early production and commercial solution launches.