AI Camera Systems Engineer

General Summary:

• We are looking for a passionate and hands-on Engineer (1–2 year's experience) to join our AI Camera Systems team at Hyderabad.
• The role focuses on building AI-driven imaging solutions for real-time embedded systems(Mobile, IOT, XR).
• You will work on development & integration of deep learning–based imaging algorithms into production camera pipelines, with strong emphasis on performance, latency, and hardware efficiency.
• This role is ideal for engineers who combine strong fundamentals in computer vision and deep learning with low-level embedded system development, and who enjoy translating AI algorithms into real-world, device-level solutions.
• You will collaborate closely with hardware, software, model, tuning, testing & customer engineering teams to deliver high-quality, scalable imaging features across the complete chipset development & commercialization life cycle.

Roles & Responsibilities

• Develop, integrate, and optimize deep learning–based imaging solutions for embedded camera systems
• Implement & optimize computer vision and image processing pipelines for real-time execution
• Work on deploying and optimizing deep learning models for imaging tasks such as enhancement, detection, segmentation and other ISP-related features
• Translate AI models into performance-optimized embedded implementations, considering memory, latency, and power constraints
• Leverage GPU, DSP, and other hardware accelerators to accelerate AI and imaging workloads
• Collaborate with model & framework teams to design hardware-aware AI solutions aligned with sensor, ISP, and SoC capabilities
• Work with embedded OS concepts including processes, threads, memory management, and scheduling
• Design, implement, and debug inter-process communication (IPC) mechanisms in complex camera systems
• Participate actively in SDLC, including requirement analysis, design reviews, development, testing, integration, debugging, and performance tuning
• Analyze and resolve system-level issues related to image quality, AI inference performance, stability, and scalability
• Strong foundation & hands-on in C, C++ & Python
• Hands-on with Qualcomm-based platforms, understanding camera subsystems, DSP offload, and SoC-level optimization, would be a plus.

Minimum Qualifications:

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