Data Science & AI Engineer

Cars24

Location

Gurugram

Employment

Full Time

Experience

0-1 years

Salary

₹Not Available

About the role

Focus on topics such as machine learning model development, natural language processing, deep learning frameworks, data analysis and manipulation, and collaboration with product and engineering teams for production deployment.

Responsibilities

Design, develop, and productionize machine learning models for business-critical use cases (pricing, fraud detection, personalization, etc.)
Implement GenAI and NLP models for summarization, classification, embeddings, and retrieval-based systems.
Build and scale deep learning models using TensorFlow or PyTorch.
Analyze and manipulate large datasets using Python (Pandas, NumPy) and visualization libraries (Matplotlib, Seaborn).
Collaborate with product and engineering teams to bring ML models into production and continuously improve them.

Full description

What will you drive? Design, develop, and productionize machine learning models for business-critical use cases (pricing, fraud detection, personalization, etc.) Implement GenAI and NLP models for summarization, classification, embeddings, and retrieval-based systems. Build and scale deep learning models using TensorFlow or PyTorch. Analyze and manipulate large datasets using Python (Pandas, NumPy) and visualization libraries (Matplotlib, Seaborn). Apply algorithms like Regression, Classification, Clustering, Tree-based models (Random Forest, Boosting, etc.) Collaborate with product and engineering teams to bring ML models into production and continuously improve them. Work with SQL for querying large datasets and integrating model outputs. Deploy ML solutions on cloud infrastructure and participate in MLOps best practices. Who are we looking for? Education: Must have at least a B.Tech/B.E. in Engineering from a reputed institution (Tier-1 preferred). MBA/M.Sc. on top of engineering is a strong plus. Candidates with BBA/B.Sc. backgrounds will not be considered. Experience: 1–3 years of full-time, hands-on data science experience. Strong understanding of model development, testing, and production deployment. Technical Skills: Solid Python skills: Pandas, NumPy, Matplotlib, Seaborn, etc. Expertise in ML and DL frameworks: TensorFlow or PyTorch. Strong understanding of ML algorithms and statistical modeling. Good foundation in mathematics, statistics, and probability. Proficiency in SQL. Exposure to cloud platforms (GCP, AWS, etc.) and scalable deployment.