About the Role

We are looking for an experienced Data Science & Machine Learning Professional with more than 5 years of expertise in Data Engineering, Data Science, and AI/ML domains. The ideal candidate should have strong technical knowledge, analytical abilities, and hands-on experience in building and deploying advanced machine learning models and AI-driven solutions.

Roles & Responsibilities

Design, develop, and implement machine learning models and algorithms such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, and Decision Forests.
Work with large-scale data frameworks such as Hadoop, PySpark, Hive, and AWS EMR for data processing.
Leverage business intelligence tools like Tableau and Power BI for data visualization and insights.
Apply AI/ML technologies using platforms such as AWS SageMaker, Azure Cognitive Services, and Google Colab.
Develop and optimize solutions using common data science libraries and frameworks (TensorFlow, Keras, PyTorch, CNTK, NumPy, Pandas).
Conduct NLP/NLG projects and work with large language models (LLMs) such as BERT, GPT, LLaMa, PaLM, BLOOM, and DALL-E.
Utilize SQL, Python, and optionally Scala, Java, or C++ for data-driven solutions.
Handle data storage and retrieval using NoSQL databases (MongoDB, Cassandra, HBase, Vector DBs).
Apply applied statistics concepts (distributions, regression, statistical testing) for model evaluation.
Collaborate in a fast-paced, cross-functional team environment to deliver AI/ML solutions.
Communicate findings and insights effectively to stakeholders with strong presentation skills.

Qualifications Required

Experience: More than 5 years in Data Engineering, Data Science, and AI/ML.
Education: UG – Any Graduate (relevant specialization preferred).
Skills:
- Strong expertise in SQL and Python (Scala/Java/C++ knowledge is an added advantage).
- Deep knowledge of machine learning algorithms and AI/ML frameworks.
- Hands-on with big data technologies and cloud-native platforms (AWS, Azure, GCP).
- Experience in NLP, NLG, and LLMs.
- Strong mathematical and analytical background (statistics, algebra, probability).
- Excellent communication, problem-solving, and business acumen skills.

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