Collect, clean, and preprocess large datasets from various sources.
Perform data wrangling, feature engineering, and handle missing or noisy data.
Work with structured (databases) and unstructured (text, images, audio) data.
Develop and implement machine learning algorithms (classification, regression, clustering, NLP, deep learning).
Build and train AI models using tools such as TensorFlow, PyTorch, scikit-learn, and Keras.
Optimize models for accuracy, speed, and scalability.
Experiment with advanced techniques like CNNs, RNNs, GANs, and Transformers.
Evaluate model performance using metrics such as accuracy, precision, recall, F1 score, etc.
Tune hyperparameters and validate results through cross-validation.
Conduct A/B testing and model explainability checks.
Deploy AI/ML models into production environments using APIs, Docker, Kubernetes, or cloud services (AWS, Azure, GCP).
Integrate models with business applications or customer-facing systems.
Maintain and monitor models post-deployment to ensure consistent performance.
Stay updated with the latest trends in AI, ML, Deep Learning, and Generative AI.
Prototype and experiment with new algorithms or architectures.
Participate in AI research projects, publications, and patent development.
Work closely with data scientists, engineers, and business analysts to understand project requirements.
Translate technical outcomes into actionable business insights.
Document AI solutions, workflows, and processes for reproducibility.
Medical Insurance: Coverage for employee and family (spouse, parents, children).
Life & Accident Insurance: Provided to all permanent employees.
Annual Health Check-ups: Free or discounted preventive tests.
Mental Health Support: Counseling, EAP programs, and wellness helplines.
Fitness Perks: Gym reimbursements, yoga and wellness sessions.
Flexible Working Hours: Choose your timing based on project requirements.
Hybrid / Remote Work Options: Many AI-ML projects support work-from-home setups.
Paid Leaves:
Annual and casual leaves
Sick leave
Maternity / Paternity leave
Optional sabbatical for long service
Comp-off: Time-off for extra hours or weekend work.
Competitive Base Pay: Among the top 10% of IT salary bands.
Performance-Linked Bonuses: Based on innovation or project delivery.
Provident Fund (PF) & Gratuity: As per statutory norms.
Insurance Coverage: Accident, life, and medical.
Employee Stock Options (ESOP / ESPP): For senior or long-term employees (available at HCL, Accenture, IBM).
Annual Salary Revisions: Based on appraisal ratings.
🏢 Company Overview Founded: 1976 by Shiv Nadar Headquarters: Noida, Uttar Pradesh, India Employees: Over 227,000 across 60 countries Key People: Roshni Nadar Malhotra (Chairperson), C Vijayakumar (CEO & Managing Director)... Read More