Experience
Up to 2 yrs
Job Location
India
Vacancy
1
Designation
AI Engineer
Job Type
Not specified
Job Description
We are looking for a passionate and talented AI Engineer (Fresher) to join our team. As an AI Engineer, you will work on cutting-edge artificial intelligence and machine learning solutions, contributing to the development of AI-driven applications and models. This is a great opportunity to start your career in AI and grow within a dynamic and innovative environment.
Key Responsibilities
- Assist in designing, developing, and deploying AI and machine learning models.
- Implement deep learning, computer vision, NLP, and other AI-based techniques.
- Collaborate with data scientists, engineers, and business teams to integrate AI solutions into products.
- Conduct experiments, fine-tune AI models, and evaluate model performance.
- Stay updated with the latest trends in AI, ML, and deep learning technologies.
- Participate in code reviews, documentation, and knowledge-sharing sessions.
Key Differentiators
Required Skills
- Strong knowledge of Python and familiarity with AI/ML libraries like TensorFlow, PyTorch, OpenCV, and Scikit-learn.
- Strong knowledge of Python and familiarity with AI/ML libraries like TensorFlow, PyTorch, OpenCV, and Scikit-learn.
- Understanding of machine learning concepts, deep learning architectures, and neural networks.
- Basic knowledge of data preprocessing, feature engineering, and model evaluation.
- Hands-on experience with SQL and NoSQL databases.
- Familiarity with cloud platforms like AWS, Azure, or Google Cloud is a plus.
- Good problem-solving skills and ability to work with unstructured data.
- Strong analytical and communication skills.
Educational Qualifications
- Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- AI/ML certifications (preferred but not mandatory).
- Preferred Qualifications (Good to Have)
- Knowledge of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Experience with AI-driven projects, Kaggle competitions, or research papers.
- Exposure to MLOps, model deployment, and AI pipelines.
- Work on real-world AI applications and projects.
- Learn from industry experts and mentors.
- Opportunity to grow and transition into senior AI roles.
- Exposure to the latest AI technologies and research.