AIML Engineer

Job Title: Machine Learning Engineer

About the Role

We are looking for a Machine Learning Engineer with expertise in YOLO, custom ML models, and deep learning to join our team. If you have 4+ years of experience in developing and deploying computer vision solutions, this is an exciting opportunity to work on cutting-edge AI applications.

Key Responsibilities

• Develop, train, fine-tune, and optimize YOLO-based object detection models (YOLOv5, YOLOv8, etc.).
• Design and implement custom ML models tailored to specific business needs.
• Handle large-scale datasets, including data collection, preprocessing, and augmentation.
• Deploy ML models in cloud environments (AWS, GCP, Azure) and edge computing

platforms (Jetson Nano, Raspberry Pi, Coral TPU, etc.).

Optimize ML models using techniques such as quantization, pruning, and model

compression.

• Evaluate and improve model performance using mAP (mean Average Precision), IoU

(Intersection over Union), precision-recall, and F1-score.

• Work closely with data scientists, software engineers, and DevOps teams to integrate

models into production systems.

• Stay updated with the latest advancements in deep learning, computer vision, and AI

model optimization.

Required Skills & Qualifications

• Minimum 4+ years of experience in Machine Learning, Deep Learning, and Computer

Vision.

• Strong expertise in YOLO-based object detection models (YOLOv5, YOLOv7, YOLOv8, etc.).
• Proficiency in Python, TensorFlow, PyTorch, and Keras.
• Experience with OpenCV, FastAPI, Flask for computer vision applications and API

deployment.

• Knowledge of ONNX, TensorRT for model deployment and optimization.
• Familiarity with Docker, Kubernetes, MLflow, Kubeflow, and Airflow for MLOps and model

lifecycle management.

• Experience working with cloud-based ML services (AWS SageMaker, Google Vertex AI, Azure ML).
• Strong understanding of CNNs, RNNs, Transformers, and other deep learning

architectures.

• Hands-on experience in dataset annotation, synthetic data generation, and image preprocessing.

Preferred Qualifications

• Experience in real-time AI applications, robotics, smart surveillance, or autonomous systems.
• Knowledge of Edge AI deployment on NVIDIA Jetson, Coral TPU, or Raspberry Pi.
• Experience with generative AI models, self-supervised learning, and synthetic data creation.
• Prior work in video analytics, smart security systems, healthcare AI, or industrial

automation.