Senior Software Engineer-Computer vision
At a glance
Senior Machine Learning Engineering role at Stryker. Gurugram · full-time.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Assess and tailor vision architectures for detection, classification, tracking and instance segmentation tasks
- Build and refine models with PyTorch, and create data preparation, augmentation and labeling workflows
- Meet latency and throughput targets by streamlining inference and applying compression or distillation
- Run active-learning cycles and monitor deployed models for data drift and failures on difficult cases
What you bring
- At least five years building computer vision models for applied research or production use
- A relevant bachelor’s degree with five years’ experience, a master’s with five years, or a doctorate with two years
- Strong Python and PyTorch or TensorFlow skills, plus working knowledge of OpenCV and NumPy
- Practical MLOps expertise and knowledge of modern CNNs, vision transformers and real-time detection architectures
Who this fits
This senior role suits an engineer who can take vision research into deployment and improve model speed under tight operating limits. The role is hybrid in Gurugram, India, and requires no travel.
From the employer
We are seeking a Computer Vision/AI Engineer to research, architect, and deploy state-of-the-art vision models for high-throughput, low-latency computer vision pipelines. In this role, you will work on problems spanning real-time object detection, multi-class classification, tracking, and instance segmentation. You will bridge cutting-edge applied research with edge/cloud production engineering—experimenting with advanced CNN backbones, Vision Transformers (ViTs), and multimodal architectures while optimizing inference speed for real-world constraint.
Technical Responsibilities
- Evaluate, benchmark, and adapt frontier vision architectures (e.g., YOLO variants, R-CNN, ViTs, Transformers, MobileNet backbones).
- Design, train, and fine-tune computer vision models using PyTorch, TorchVision etc.
- Architect data preprocessing, augmentation and annotation workflows for imbalanced and noisy visual datasets.
- Optimize deep learning models for strict latency/throughput budgets using TensorRT, ONNX Runtime, DeepStream etc.
- Apply model compression techniques including post-training quantization (INT8/FP16) and knowledge distillation.
- Implement active learning loops and continuous monitoring systems to track data drift and edge-case model failures in production.
Minimum Qualification
- Bachelor's degree in software engineering/ Computer Science or related discipline with 5+ years of work experience or Master’s in relevant disciplines with 5+ years of experience or PhD degree in relevant disciplines with 2+ years of work experience.
Preferred Qualifications
- 5+ years hands-on experience designing and training computer vision models in production or applied research environments.
- Proficiency in Python and PyTorch (or TensorFlow); solid foundation in OpenCV and NumPy.
- Proficiency in end-to-end MLOps practices.
- In-depth theoretical and practical grasp of
- Classic & modern CNNs (ResNet, EfficientNet, ConvNeXt).
- Vision Transformers & attention mechanisms (ViT, Swin, DETR, RT-DETR).
- Modern real-time detector architectures (YOLO*, RT-DETR, SSD).
- Excellent communication skills with the ability to work cross-team.
Good to have
Experience with video streaming protocols and pipelines (RTSP, WebRTC, GStreamer, FFmpeg, or NVIDIA DeepStream).
Travel Percentage: None