Urgent Hiring || Senior ML Engineer – Computer Vision & Image Recognition || Hyderabad ||

Location- Hyderabad

Profile- Senior ML Engineer – Computer Vision & Image Recognition

Experience-7 Years

Ctc- upto 28 lpa (Depends on interview)

Working days- 5 days (9:30am- 5:30 pm)

About the Role

We're hiring a top-class ML Engineer with deep expertise in Computer Vision - someone who can fine-tune SOTA models, build custom architectures from scratch when needed, and ship production-grade systems. You'll have access to a great pool of AI native talent within an AI native company, working on cutting edge tools and projects with strong exposure to the latest in AI driven analytics.

Must-Have Skills

- Independently take a CV problem from requirement to deployed, optimized, monitored production system - including designing
- current architectures when off-the-shelf models don't fit. Strong enough to justify every model/fine-tuning decision mathematically and
- technically.
- Education
- 7+ yrs in ML/AI, full lifecycle (data -> model -> production)
- Strong mathematical foundation: linear algebra, probability & statistics, calculus/optimization theory, and the ability to
- derive/reason about model behavior (not just apply libraries)




- Fine-tuning AND building models from scratch on top vision architectures:
- ResNet, EfficientNet, MobileNet
- YOLO, Faster R-CNN, DETR
- U-Net, Mask R-CNN, SAM
- ViT, Swin Transformer, CLIP
- Strong in classification, detection, segmentation, tracking and real-time video stream analytics
- Ability to design custom model architectures for novel/non-standard requirements — not limited to fine-tuning existing ones
- Python, PyTorch/TensorFlow, OpenCV — expert level
- Model evaluation: mAP, IoU, precision/recall, F1
- Experience taking models to production (APIs, containers, monitoring)
- MLOps: versioning, CI/CD, drift monitoring
- Willingness to learn and adopt AI tools within an advanced, AI native work ecosystem, including comfort using AI assisted
- analysis, copilots, and emerging AI driven workflows as part of daily work
- - Good-to-Have
- - Edge AI deployment (Jetson, Raspberry Pi, Qualcomm)
- Model optimization: quantization, pruning, distillation, ONNX, TensorRT, OpenVINO
- MLflow, Kubeflow, DVC, Airflow
- Docker, Kubernetes, Cloud (AWS/Azure/GCP)
- GenAI, VLMs, multimodal/foundation models

Education

CS/AI/ML/Data Science/Math/Stats degree or equivalent experience.

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