- Design and develop machine learning pipelines for classification, regression, and NLP tasks.

- Implement and experiment with different machine learning algorithms and techniques, including supervised, unsupervised, and deep learning.

- Pre-process and clean large datasets for model training and evaluation.

- Train, evaluate, and optimize machine learning models using frameworks like TensorFlow, PyTorch, scikit-learn, and LangChain.

- Integrate machine learning models into production systems and monitor their performance.

- Develop machine learning pipelines for computer vision tasks, including object detection, image classification, and image segmentation.

- Implement and experiment with different machine learning algorithms specific to computer vision, such as convolutional neural networks (CNNs).

- Collaborate with data scientists, software engineers, and other stakeholders to develop and deploy machine learning solutions, particularly focusing on computer vision and LLM applications.

- Communicate complex technical concepts to non-technical audiences.

- Utilize cloud platforms (AWS, GCP, Azure) for deploying machine learning models.

- Apply database knowledge to efficiently store, retrieve, and manage large datasets used for training and evaluating models.

Required Skills & Qualifications:

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

- Minimum 4+ years of experience in AI/ML development.

- Strong proficiency in Python and machine learning frameworks (TensorFlow, PyTorch, scikit-learn, LangChain).

- Experience in NLP, computer vision, and deep learning.

- Hands-on experience with cloud platforms (AWS, GCP, Azure) for AI/ML deployment.

- Familiarity with databases and efficient data handling techniques.

- Strong problem-solving and analytical skills.