Ai/ml/dl Computer Vision Intern

6 days ago

Remote, India Mexilet Technologies Private Limited Full time

**Responsibilities**:

- Assist in designing, training, and optimizing deep learning models for computer vision tasks (e.g., object detection, segmentation, classification).
- Work with large image and video datasets — preprocessing, augmentation, and annotation.
- Implement and experiment with state-of-the-art architectures using frameworks like TensorFlow, PyTorch, or OpenCV.
- Collaborate with data scientists and engineers to deploy models in real-world scenarios.
- Evaluate model performance using metrics such as precision, recall, F1-score, and accuracy.
- Research recent advancements in AI/ML and propose innovative solutions.
- Document project progress, results, and technical approaches.

**Requirements**:

- Strong understanding of **Machine Learning**, **Deep Learning**, and **Computer Vision** fundamentals.
- Familiarity with frameworks such as **TensorFlow**, **PyTorch**, **Keras**, and **OpenCV**.
- Programming experience in **Python**.
- Knowledge of neural network architectures like CNNs, RNNs, or Transformers.
- Experience with dataset handling, image processing, and model evaluation.
- Currently pursuing or recently completed a degree in **Computer Science**, **AI/ML**, **Data Science**, or a related field.

**Preferred Skills (Optional)**:

- Experience with cloud platforms (AWS, Google Cloud, Azure).
- Exposure to edge AI or model deployment tools (TensorRT, ONNX, etc.).
- Knowledge of NLP or multimodal learning.

**Benefits**:

- Hands-on experience working with real-world AI/ML projects.
- Mentorship from experienced professionals in the AI domain.
- Internship certificate on successful completion.
- Potential opportunity for full-time placement based on performance.

**Job Types**: Full-time, Part-time, Fresher, Internship, Freelance
Contract length: 3 months

Pay: ₹3,000.00 - ₹6,000.00 per year

Expected hours: 56 per week

**Benefits**:

- Flexible schedule
- Paid sick time
- Work from home

Work Location: Remote

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