Machine Learning Engineer

Job Title: Machine Learning Engineer – Vision Models

AI/ML Research & DevelopmentRupa Solitaire , Navi Mumbai, Mahape

Experience Required: 5–8 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

• mage classification using ResNet, EfficientNet, ConvNeXt
• Object detection using ResNet + FPN, EfficientDet, MobileNet (SSD, YOLO backbones)
• Image segmentation using UNet (CNN-based), DeepLab (ResNet/Xception backbone)
• ML , Computer visison & Ai
• Design and implement deep learning models for:
• Image classification using ResNet, EfficientNet, ConvNeXt
• Object detection using ResNet + FPN, EfficientDet, MobileNet (SSD, YOLO backbones)
• 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

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field

Thanks & Regards

Swati Bhardwaj

talentacquisition3.swati@blueocean.systems

9729223983

BlueOceanSystems

Job Type: Full-time

Pay: ₹624,277.54 - ₹2,080,191.37 per year

Work Location: In person