Skills:
Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Gen AI, RAG, AI/ML, Data science,
Key Responsibilities
Model Development & Optimization
- Design, develop, and deploy advanced deep learning models (CNN, RNN, LSTM, Transformers)
- Build scalable AI solutions for real-world business problems
- Perform feature engineering, hyperparameter tuning, and model optimization
- Implement transfer learning and fine-tuning of pre-trained models
- Improve model accuracy, efficiency, and scalability
Data Engineering & Processing
- Work with large structured and unstructured datasets
- Develop data pipelines for training and inference workflows
- Perform exploratory data analysis (EDA) and statistical analysis
- Ensure data quality, validation, and governance
Deployment & MLOps
- Deploy models into production using APIs and containerization tools
- Work with Docker, Kubernetes, and CI/CD pipelines
- Monitor model performance and retrain models when necessary
- Collaborate with DevOps teams for scalable deployment
AI Frameworks & Technologies
- Strong hands-on experience with Python
- Expertise in TensorFlow and/or PyTorch
- Experience with Scikit-learn, NumPy, Pandas
- Exposure to cloud platforms (AWS / Azure / GCP)
- Knowledge of distributed computing frameworks is an added advantage
Collaboration & Leadership
- Work closely with product managers, engineers, and stakeholders
- Translate business problems into data science solutions
- Mentor junior data scientists and review code/models
- Present insights and model results to technical and non-technical audiences
Required Skills & Experience
- 6+ years of experience in Data Science / Machine Learning
- Strong expertise in Deep Learning architectures (CNN, RNN, LSTM, Transformers)
- Experience in model deployment and MLOps practices
- Solid understanding of statistics, probability, and linear algebra
- Experience handling large-scale datasets
- Strong problem-solving and analytical skills
