Job Title : Machine Learning Engineer Vision Models

Department : AI/ML Research & Development

Location : Rupa Solitaire , Navi Mumbai, Mahape

Employment Type : Full-time

Experience Required : 5- 10 years

Job Summary :

We are seeking a Machine Learning Engineer with hands-on experience in designing, training, and deploying deep learning models for computer vision tasks. The ideal candidate will be proficient in image classification, object detection, and segmentation using state-of-the-art architectures, and capable of optimizing models for embedded and mobile platforms.

Key Responsibilities :

- Design and implement deep learning models for :

1. Image classification using ResNet, EfficientNet, ConvNeXt

Experience in 3 D image processing, Image classification & object detection is prefered.

2. Object detection using ResNet + FPN, EfficientDet, MobileNet (SSD, YOLO backbones)

3. Image segmentation using UNet (CNN-based), DeepLab (ResNet/Xception backbone)

- Apply transfer learning techniques using VGG, ResNet, EfficientNet

- Optimize models for embedded/mobile deployment using MobileNet, ShuffleNet, EfficientNet-Lite

- Preprocess and annotate datasets for supervised learning pipelines

- Conduct model evaluation, hyperparameter tuning, and performance benchmarking

- Collaborate with data engineers, software developers, and product teams for integration and deployment

- Document experiments, model architectures, and training workflows

Mandatory Skills :

- Strong proficiency in Python and deep learning frameworks : PyTorch, TensorFlow

- Experience with CNN architectures and vision-specific models

- Familiarity with OpenCV, NumPy, Pandas

- Hands-on with model training, fine-tuning, and inference optimization

- Knowledge of transfer learning, data augmentation, and loss functions

- Experience with Linux, Git, and Docker

Preferred / Good-to-Have Skills :

- Exposure to ONNX, TensorRT, or TFLite for model conversion and deployment

- Experience with CVAT, Label Studio, or similar annotation tools

- Familiarity with MLOps, Kubernetes, or cloud-based ML pipelines

- Understanding of embedded systems, edge AI, or mobile inference

- Knowledge of multi-modal datasets (e.g., image + sensor data)

Qualifications :

- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field