Computer Vision Engineer

About Company, Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction. Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients. Join us to challenge yourself and accomplish work that matters. We’re hiring Computer Vision Engineer in Gurugram, Haryana, India We are seeking a Computer Vision Software engineer with a strong foundation in machine learning, real-time vision systems, and edge deployment optimization. The ideal candidate will bring 5-8 years of experience in architecting scalable, production-grade CV solutions with a deep understanding of image segmentation, object classification, and model acceleration techniques. This role involves designing end-to-end vision pipelines that operate in low-latency, constrained environments, and building robust perception systems for object interaction and classification tasks in structured visual environments. Key Responsibilities Model Development & Optimization - Implement deep learning models for object detection, instance segmentation, and classification in structured visual domains. - Develop and optimize models for real-time inference on edge devices using tools like TensorRT, ONNX, NVIDIA Jetson, and CUDA. - Apply advanced techniques for model compression, quantization, and pruning to meet performance constraints. System Architecture - Design and own the entire computer vision pipeline: from camera capture to final inference output. - Ensure low-latency performance, particularly on embedded or GPU-powered edge hardware. - Benchmark and profile model performance using tools like NVIDIA Nsight, trtexec, or custom profilers. Data Engineering & Image Processing - Drive dataset curation, augmentation, and labeling strategies for diverse object classes. - Develop efficient preprocessing and postprocessing pipelines, including noise reduction, image enhancement, and perspective correction. Deployment & Productionization - Integrate models into production environments with CI/CD and ML Ops pipelines. - Ensure secure, efficient, and fault-tolerant deployment of models on embedded systems or cloud-edge hybrids. Research & Innovation - Stay current with the latest trends in deep learning, vision transformers, diffusion models, and real-time inference. - Evaluate research papers and contribute to internal innovation through POCs and rapid prototyping. Required Skills & Experience - 3-6 years of industry experience in computer vision and machine learning, with at least 3–5 years in an architect or technical leadership role. - Expert in Python, with strong experience in OpenCV, PyTorch, and/or TensorFlow. - Strong grasp of deep learning concepts: CNNs, attention mechanisms, image segmentation, small-object detection. - In-depth knowledge of image processing, perspective warping, homography, and visual tracking. - Hands-on experience with model optimization and deployment using TensorRT, ONNX, CUDA, and Jetson platforms. - Proficient in tools like Docker, Git, and MLFlow or other model tracking/versioning frameworks. - Solid foundation in linear algebra, calculus, probability, and statistics. - Demonstrated experience in building CV systems for real-time applications, especially on edge hardware. Preferred Qualifications - Prior experience developing perception systems for structured, rule-based environments (e.g., card games, tabletop detection, automated gameplay, etc.) - Knowledge of hardware-aware training, mixed-precision inference, or vision transformers - Experience with C++/CUDA kernels for custom ops or performance enhancement - Published papers, patents, or open-source contributions in the CV/ML space Soft Skills - Strong problem-solving mindset and ability to work in ambiguous, fast-paced environments - Excellent communication and technical documentation skills - Ability to mentor junior engineers and collaborate across disciplines Bonus Tools / Stack Exposure - TensorRT, ONNX, Jetson Nano/Xavier, NVIDIA Nsight - DeepStream SDK, OpenVINO - FastAPI / Flask for exposing inference APIs - GStreamer, FFmpeg for video pipeline optimization - DVC, ClearML, or similar experiment tracking tools Droisys is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Droisys believes in diversity, inclusion, and belonging, and we are committed to fostering a diverse work environment