About the role
We are looking for passionate and curious AI/ML Engineers (Freshers) with hands-on experience in machine learning and deep learning. You'll contribute to the development of intelligent systems, working with real-world datasets and modern ML frameworks.
Key Responsibilities:
Build and train machine learning and deep learning models using TensorFlow, PyTorch, and scikit-learn.
Work with structured and unstructured data using Pandas, NumPy, and SQL.
Develop and fine-tune Natural Language Processing (NLP) pipelines and explore LLMs (like GPT, BERT).
Implement computer vision models using OpenCV and related tools.
Collaborate with data scientists and engineers to develop scalable ML solutions.
Participate in data preprocessing, feature engineering, model evaluation, and deployment.
Contribute to experiments, documentation, and version control (Git).
Technical Skills:
Proficient in Python and common data/ML libraries (Pandas, NumPy, Scikit-learn).
Solid understanding of machine learning and deep learning concepts.
Hands-on with frameworks like PyTorch, TensorFlow, Keras.
Experience with SQL and working with databases.
Exposure to OpenCV for computer vision projects.
Knowledge of NLP techniques, transformer models, and LLMs is a big plus.
Familiarity with APIs, Jupyter notebooks, and model deployment pipelines is preferred.
AWS knowledge is a plus.
Eligibility & Requirements:
Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related fields.
Strong analytical thinking and problem-solving mindset.
Practical experience via projects, internships, hackathons, or research work.
Excellent communication skills and team spirit.
Nice to Have:
GitHub or Kaggle profile with projects or contributions.
Understanding of cloud platforms (AWS, GCP, Azure) for ML workflows.
Awareness of MLOps tools and practices.
What We Offer:
Work on real-world AI/ML problems with mentorship.
Continuous learning environment with upskilling opportunities.
Chance to experiment with cutting-edge technologies like LLMs.
Supportive, growth-driven team culture.
