Develop and implement scalable machine learning, deep learning, and NLP models.
Train, fine-tune, and deploy Large Language Models (LLMs) such as GPT, BERT, and transformer-based architectures.
Perform data preprocessing, feature engineering, and data wrangling using structured and unstructured datasets.
Build predictive models using frameworks like TensorFlow, PyTorch, Keras, and scikit-learn.
Deploy ML models into production environments with best practices in performance, monitoring, and scalability.
Work with cloud platforms such as AWS, Azure, or Google Cloud for model development and deployment.
Collaborate with cross-functional teams to understand business problems and translate them into technical solutions.
Utilize data visualization tools like Tableau, Matplotlib, or dashboarding tools such as Flask / Streamlit.
Use version control (Git) and containerization tools such as Docker for efficient development.
Prepare business presentations, storyboards, and reports to communicate insights and model outcomes.
Requirements: Education
Master's degree in Statistics, Mathematics, Computer Science, or related field OR
MBA with specialization in Data Science / AI / Analytics.
Technical Skills
2-8 years of hands-on industry experience in AI / ML.
Strong programming skills in Python; knowledge of R, Java, or C++ is an added advantage.
Strong understanding of ML, Deep Learning, NLP, neural networks (CNN, RNN, Transformers).
Experience deploying ML models in production.
Experience with databases: MySQL, PostgreSQL, MongoDB.
Solid understanding of data structures, algorithms, and distributed computing.
Cloud platform familiarity: AWS / Azure / GCP.
Good knowledge of visualization and dashboarding tools.
Job Types: Full-time, Permanent, Contractual / Temporary
Pay: ?500,000.00 - ?1,700,000.00 per year
Benefits:
Provident Fund
Experience:
Data Scientist: 4 years (Required)
MySQL, PostgreSQL, MongoDB: 4 years (Required)
ML, Deep Learning, NLP, neural networks : 4 years (Required)
Java , Python , C++: 4 years (Required)
* AI & Machine Learning: 4 years (Required)
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