Computer Vision Engineer

3 days ago

Greater Hyderabad Area, India KYNEA SOLUTIONS LLP Full time US$ 1,20,000 - US$ 2,00,000 per year

As a Machine Learning Engineer specializing in Generative AI work, you will play a critical role in advancing our AI capabilities, contributing to our product development, and driving innovation. You will help in building a team of data scientists, engineers, and researchers to create groundbreaking solutions in the field of Generative AI.

Key Responsibilities:

  1. Design and Deploy Generative AI solutions: Lead the design, development, training, and deployment of Generative AI models to address specific business and product challenges

  2. Research and Innovation: Stay up-to-date with the latest advancements in Generative AI, and identify opportunities for innovative applications within our domain

  3. Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and domain experts, to define project objectives and translate business needs into AI solutions

  4. Data Preparation: Guide and Collaborate with the legal team in data acquisition, preprocessing, and labeling to ensure high-quality training datasets

  5. Model Optimization: Optimize and fine-tune models to meet performance, scalability, and efficiency requirements

  6. Validation and Testing: Implement robust testing procedures and validation metrics to ensure the quality and reliability of Generative AI solutions

  7. Deployment and Integration: Collaborate with the engineering team to integrate AI models into our products and services.

KEY REQUIREMENTS:

  • Proven experience with Generative AI models (GANs, VAEs, Transformers).
  • Strong proficiency in ML frameworks such as TensorFlow, PyTorch, or Keras.
  • Expertise in data preprocessing, feature engineering, model training, and hyperparameter tuning.
  • Proficiency in Python, with hands-on experience in scientific libraries (NumPy, Pandas, SciPy, scikit-learn, Matplotlib, Seaborn).
  • Solid understanding of object detection techniques (YOLO, Faster R-CNN, SSD, RetinaNet, etc.) and real-time image/video processing.
  • Experience building and fine-tuning CNNs, RNNs, and transformer-based models for computer vision tasks.
  • Strong knowledge of Computer Vision fundamentals: image classification, segmentation (semantic & instance), tracking, OCR, and 3D vision.
  • Hands-on experience with OpenCV and related libraries for practical CV solutions.
  • Ability to design, train, and optimize custom deep learning architectures for object detection and recognition.
  • Strong foundation in Data Science concepts — statistical modeling, exploratory data analysis, visualization, and predictive analytics.
  • Experience in building data pipelines and handling large-scale, unstructured datasets.
  • Experience deploying ML/CV models into production (Docker, REST APIs, or cloud-based endpoints).
  • Familiarity with cloud computing platforms (AWS, Azure, GCP) and distributed training frameworks.
  • Knowledge of GPU acceleration, performance optimization, and parallel computing.
  • Excellent problem-solving, debugging, and optimization skills.
  • Ability to work in a fast-paced startup environment and collaborate with cross-functional teams.
  • Excellent communication skills to convey technical concepts clearly.
  • Experience with Natural Language Understanding (NLU) is a plus.

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