Junior–Mid Level AI/ML Engineer

1 week ago

⚠️ Before applying, please carefully review all the job requirements

Job Overview

Swatitech is seeking a Junior–Mid Level AI/ML Engineer specializing in Computer Vision to join its technical team and construct practical vision intelligence applications. This role centers on processing image streams and video feeds to build functional machine learning systems capable of object detection, image classification, semantic segmentation, pose estimation, and object tracking.
Engineers in this role will work across the full model lifecycle using technologies such as Python, PyTorch, TensorFlow, OpenCV, YOLO, and convolutional neural networks (CNNs). Key responsibilities include curating and augmenting vision datasets, executing transfer learning with pretrained benchmark models, conducting performance evaluations, optimizing models for edge hardware, and deploying production-ready REST services.

★ Architect, train, and maintain machine learning models for object detection, classification, segmentation, pose estimation, and tracking.
★ Curate, annotate, and augment large-scale image and video datasets to support model training workflows.
★ Adapt and fine-tune pretrained deep learning models using transfer learning techniques on standard benchmarks like ImageNet and COCO.
★ Conduct comprehensive quantitative evaluations using mAP, IoU, precision, recall, and error analysis.
★ Optimize model inference speed and efficiency utilizing TensorRT, ONNX, quantization, pruning, and edge execution strategies.
★ Deploy production-ready computer vision solutions using Docker containers, REST APIs, and GPU or edge computing infrastructure.

★ 1 to 3 years of experience in AI/ML or Computer Vision, or equivalent hands-on project experience.
★ Technical proficiency in Python along with deep learning frameworks such as PyTorch or TensorFlow.
★ Core working knowledge of computer vision tools and architectures, including OpenCV, YOLO, and Convolutional Neural Networks (CNNs).
★ Practical experience with image and video dataset curation, annotation, and data augmentation techniques.
★ Familiarity with fine-tuning pretrained architectures using transfer learning on datasets such as COCO and ImageNet.
★ Knowledge of model performance metrics including mAP, IoU, precision, and recall.
★ Exposure to model optimization frameworks and techniques including TensorRT, ONNX, quantization, and pruning.
★ Ability to deploy models into production using Docker, RESTful APIs, and GPU/edge environments.

This role may be suitable for candidates who are early- to mid-career machine learning professionals or software developers specializing in visual intelligence. Applicants who have built a strong foundation through 1 to 3 years of professional experience or through an extensive portfolio of computer vision projects will find this opportunity well aligned with their technical skill set. It is an ideal fit for engineers who enjoy working across the complete machine learning pipeline—from dataset preparation and neural network fine-tuning to edge optimization and containerized deployment.

Applicants may want to highlight a dedicated Computer Vision portfolio or GitHub repositories showcasing real-world model implementation and deployment. Detailing specific projects involving object detection, tracking, or segmentation using tools like YOLO, OpenCV, or PyTorch can help demonstrate practical expertise. In your CV, emphasizing experience with dataset annotation, model compression techniques (such as ONNX or TensorRT), or containerization with Docker and REST APIs will clearly convey your readiness for production-level AI engineering tasks.

Submit CV and Portfolio via Email: recruiting@swatitech.com