𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟯𝟴𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟮𝟬-𝟯𝟴 𝗟𝗣𝗔) Experience: 6+ yrs Location: Pune, Maharashtra, India Job Type: Full-time We are looking for an experienced AI/ML Engineer with 6+ years of experience in Data Science, Machine Learning, and Python to design, develop, and deploy intelligent, data-driven solutions. The role requires strong expertise in machine learning algorithms, statistical analysis, data processing, model development, and productionisation of AI/ML solutions. The ideal candidate will combine strong Data Scientist capabilities with hands-on engineering skills to solve complex business problems using data. You will work across the machine learning lifecycle, from data exploration and feature engineering through model development, evaluation, deployment, monitoring, and continuous improvement. Requirements Key Responsibilities Design, develop, test, and deploy Machine Learning models for business and product use cases. Apply Data Science techniques to analyze structured and unstructured datasets and identify actionable insights. Use Python extensively for data processing, statistical analysis, feature engineering, model development, and automation. Perform exploratory data analysis and identify trends, patterns, anomalies, and relationships within complex datasets. Develop and evaluate supervised and unsupervised machine learning models, including classification, regression, clustering, and forecasting techniques. Perform feature engineering, feature selection, model tuning, and validation to improve model performance. Define appropriate evaluation metrics and establish robust model validation and experimentation practices. Translate business problems into analytical and machine learning problems with clear objectives and measurable outcomes. Build reusable data and machine learning pipelines to support experimentation and production deployment. Collaborate with Data Engineers to prepare reliable datasets and scalable data-processing workflows. Work with software engineers to integrate machine learning models into production applications and services. Monitor deployed models and identify opportunities for performance, accuracy, and reliability improvements. Conduct experiments, document findings, and communicate analytical results to technical and non-technical stakeholders. Implement appropriate practices for data quality, model governance, reproducibility, and documentation. Stay current with emerging AI, Machine Learning, Data Science, and Python technologies and industry practices. What Makes You a Great Fit 6+ years of professional experience in Data Science, Machine Learning, AI/ML Engineering, or a closely related field . Strong hands-on expertise in Python for data analysis, machine learning, automation, and production development. Strong understanding of Machine Learning algorithms, statistical methods, model evaluation, and predictive analytics . Proven experience developing, tuning, validating, and deploying machine learning models. Strong Data Science fundamentals, including EDA, feature engineering, data preprocessing, experimentation, and statistical analysis . Experience with Python libraries such as Pandas, NumPy, Scikit-learn , and relevant machine learning frameworks. Good understanding of supervised and unsupervised learning techniques and their practical applications. Experience working with large datasets, data pipelines, and structured or unstructured data. Strong SQL skills and experience working with relational or analytical databases. Familiarity with MLOps, model deployment, monitoring, CI/CD, Docker, or cloud platforms is an advantage. Strong analytical and problem-solving skills with the ability to translate complex business requirements into practical ML solutions. Excellent communication skills and the ability to present technical findings clearly to diverse stakeholders. Strong ownership, attention to detail, and ability to work independently in a fast-paced environment. Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related discipline is preferred.