Junior Deep Learning Engineer - NLP/Computer Vision (1-2 yrs)

Job Overview :

We are looking for a passionate Junior Deep Learning Engineer with a foundational understanding of Computer Vision and Natural Language Processing (NLP). In this role, you will assist in designing, training, and deploying machine learning models while gaining hands-on experience with cutting-edge AI technologies.

Responsibilities :

- Assist in developing and fine-tuning deep learning models for tasks like image classification, object detection, text classification, and sentiment analysis.

- Work with existing architectures such as CNNs, Transformers, and RNNs, while exploring ways to improve model performance.

- Preprocess and handle large-scale datasets, including images and text, to prepare them for model training.

- Evaluate model performance using appropriate metrics and recommend improvements.

- Contribute to deploying trained models in production environments.

- Collaborate with senior engineers, data scientists, and cross-functional teams to align project goals.

- Stay updated on emerging trends in AI, particularly in computer vision and NLP.

- Document experiments, workflows, and results to ensure reproducibility and knowledge sharing.

Requirements :

- Bachelor's degree in Computer Science, AI, Machine Learning, or a related field.

- 1-2 years of hands-on experience in deep learning, with exposure to computer vision or NLP projects (academic projects or internships count).

- Familiarity with deep learning frameworks like PyTorch or TensorFlow.

- Basic understanding of neural network architectures (e.g., CNNs, RNNs, Transformers).

- Experience with computer vision libraries like OpenCV or YOLO, and NLP libraries like spaCy, NLTK, or Hugging Face Transformers.

- Proficiency in Python and data analysis libraries like NumPy, Pandas, and Matplotlib.

- Exposure to handling datasets and data preprocessing techniques for both vision and text tasks.

- Knowledge of version control systems like Git.

- Strong problem-solving skills and eagerness to learn from senior team members.

Preferred Skills :

- Hands-on experience with at least one real-world project in computer vision or NLP.

- Familiarity with tools for deploying models in production environments (e.g., Docker).

- Exposure to cloud platforms (e.g., AWS, GCP, or Azure) for training or deploying models.

- Experience with MLOps practices or tools like MLflow or Kubeflow is a plus.

- Knowledge of optimization techniques to improve model performance.

What We Offer :

- Mentorship from experienced AI engineers and data scientists.

- Opportunities to work on impactful, real-world AI projects.

- A supportive environment for continuous learning, including access to courses, conferences, and research papers.