C++ Engineer (Computer Vision)

Location: Gurugram Work Mode: Work From Office

Make Computer Vision run faster, smarter, and at scale.

Awiros is a Series A-funded deep-tech company ( ~$7M raised) building the world's first app-based Operating System for Computer Vision.

Founded in 2015, our platform enables developers and enterprises to build, deploy, and scale AI-powered video applications across edge and cloud environments.

We work at the intersection of Computer Vision, Deep Learning, C++, GPU computing, and distributed systems, building technology that processes real-time video and high-throughput workloads in real-world deployments.

At Awiros, Computer Vision isn't just about building a model that works. It's about making that intelligence fast, efficient, reliable, and production-ready.

**THE ROLE:**We're looking for a C++ Computer Vision Engineer to build and optimize the systems that bring Computer Vision algorithms into production. You'll work at the intersection of Computer Vision algorithms and high-performance software engineering

• implementing vision pipelines, integrating AI models, optimizing inference, and building efficient components for real-time video analytics. You'll work closely with our Computer Vision, AI, Platform, and Systems teams to take solutions from algorithm to deployment, with a strong focus on performance, reliability, and real-world constraints.

WHAT YOU'LL WORK ON:

• Design and develop high-performance Computer Vision components and video processing pipelines in C
• Implement and optimize algorithms for object detection, tracking, recognition, segmentation, image processing, and other video analytics use cases.
• Integrate Deep Learning models into production inference pipelines.
• Optimize AI/CV workloads for latency, throughput, memory utilization, and compute efficiency.
• Work with GPU-accelerated inference and frameworks such as TensorRT, CUDA, or similar technologies.
• Profile applications, identify bottlenecks, and improve system-level performance.
• Work with model artifacts such as ONNX and integrate them into C++ inference pipelines.
• Build robust solutions for real-time video processing and large-scale deployments.
• Debug issues across the algorithm, application, inference, and hardware layers.
• Collaborate with Computer Vision and Platform engineers to integrate CV components into the broader Awiros ecosystem.
• Take ownership of features from implementation → optimization → integration → deployment.

WHAT YOU BRING: Must Have

• Strong programming skills in C
• Strong understanding of Data Structures, Algorithms, and Object-Oriented Programming.
• Solid understanding of Computer Vision fundamentals.
• Hands-on experience with OpenCV or similar Computer Vision libraries.
• Understanding of image and video processing concepts such as image transformations, filtering, feature extraction, detection, tracking, and segmentation.
• Strong debugging and problem-solving skills.
• Experience developing production-quality software, not just academic implementations.

Good to Have

• Experience with CUDA and GPU programming.
• Experience with TensorRT, ONNX Runtime, OpenVINO, or similar inference frameworks.
• Experience working with ONNX model integration and optimization.
• Understanding of Deep Learning models and inference pipelines.
• Experience with multi-threading, concurrency, or parallel programming in C
• Exposure to Linux-based development and performance profiling.
• Familiarity with technologies such as Docker, Kubernetes, Kafka, or distributed systems.
• Experience working with real-time video or edge computing.

• Strong programming skills in C
• Strong understanding of Data Structures, Algorithms, and Object-Oriented Programming.
• Solid understanding of Computer Vision fundamentals.
• Hands-on experience with OpenCV or similar Computer Vision libraries.
• Understanding of image and video processing concepts such as image transformations, filtering, feature extraction, detection, tracking, and segmentation.
• Strong debugging and problem-solving skills.
• Experience developing production-quality software, not just academic implementations.