Trupti Solutions

Job Summary : We are looking for a versatile and results-driven Data Scientist / Machine Learning Developer with 7+ years of experience to join our dynamic team.The ideal candidate will have a strong background in both data science and machine learning, capable of handling end-to-end processes from data analysis and feature engineering to model deployment and monitoring.This role demands a proactive and collaborative mindset, working closely with product owners and engineering teams to deliver scalable, production-ready ML solutions.You will take ownership of the entire model lifecycle driving experimentation, validation, deployment, and continuous optimization to create high-impact, AI-powered business value.Job Type : Hybrid, Full-Time.Primary Work Location : Pune.In this Role, Your Responsibilities Will Be : - Develop, train and deploy machine learning, deep learning AI models for a variety of business use cases such as classification, prediction, recommendation, NLP and Image Processing.- Design and implement end-to-end ML workflows from data ingestion and preprocessing to model deployment and monitoring.- Collect, clean, and preprocess structured and unstructured data from multiple sources using industry-standard techniques such as normalization, feature engineering, dimensionality reduction, and optimization.- Perform exploratory data analysis (EDA) to identify patterns, correlations, and actionable insights.- Apply advanced knowledge of machine learning algorithms including regression, classification, clustering, decision trees, ensemble methods, and neural networks.- Use Azure ML Studio, TensorFlow, PyTorch, and other ML frameworks to implement and optimize model architectures.- Perform hyperparameter tuning, cross-validation, and performance evaluation using industry-standard metrics to ensure model robustness and accuracy.- Integrate models and services into business applications through RESTful APIs developed using FastAPI, Flask or Django.- Build and maintain scalable and reusable ML components and pipelines using Azure ML Studio, Kubeflow, and MLflow.- Enforce and integrate AI guardrails : bias mitigation, security practices, explainability, compliance with ethical and regulatory standards.- Deploy models in production using Docker and Kubernetes, ensuring scalability, high availability, and fault tolerance.- Utilize Azure AI services and infrastructure for development, training, inferencing, and model lifecycle management.- Support and collaborate on the integration of large language models (LLMs), embeddings, vector databases, and RAG techniques where applicable.- Monitor deployed models for drift, performance degradation, and data quality issues, and implement retraining workflows as needed.- Collaborate with cross-functional teams including software engineers, product managers, business analysts, and architects to define and deliver AI-driven solutions.- Communicate complex ML concepts, model outputs, and technical findings clearly to both technical and non-technical stakeholders.- Stay current with the latest research, trends, and advancements in AI/ML and evaluate new tools and frameworks for potential adoption.- Maintain comprehensive documentation of data pipelines, model architectures, training configurations, deployment steps, and experiment results.- Drive innovation through experimentation, rapid prototyping, and the development of future-ready AI components and best practices.- Write modular, maintainable, and production-ready code in Python with proper documentation and version control.- Contribute to building reusable components and ML accelerators.Qualifications : - Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related field over 7+ years.- Proven experience as a Data Scientist, ML Developer, or in a similar role.- Strong command of Python and ML libraries (e.g., Azure ML Studio, scikit-learn, TensorFlow, PyTorch, XGBoost).- Data Engineering : Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer).- ML Model Development : Strong grasp of statistical modelling, supervised/unsupervised learning, time-series forecasting, and NLP.- Proficiency in Python.- Strong knowledge of machine learning algorithms, frameworks (e.g., TensorFlow, PyTorch, scikit-learn), and statistical analysis techniques.- Proficiency in programming languages such as Python, R, or SQL.- Experience with data preprocessing, feature engineering, and model evaluation techniques.- MLOps & Deployment : Hands-on experience with CI/CD pipelines, model monitoring, and version control.- Familiarity with cloud platforms (e.g., Azure (Primarily), AWS and deployment tools.- Knowledge of DevOps platform.- Excellent problem-solving skills and attention to detail.- Strong communication and collaboration skills, with the ability to work effectively in a team environment.Preferred Qualifications : - Proficiency in Python, with libraries like pandas, NumPy, scikit-learn, spacy, NLTK and Tensor Flow, Pytorch.- Knowledge of natural language processing (NLP) and custom/computer, YoLo vision techniques.- Experience with Graph ML, reinforcement learning, or causal inference modeling.- Familiarity with marketing analytics, attribution modelling, and A/B testing methodologies.- Working knowledge of BI tools for integrating ML insights into dashboards.- Hands on MLOps experience, with an appreciation of the end-to-end CI/CD process.- Familiarity with DevOps practices and CI/CD pipelines.- Experience with big data technologies (e.g., Hadoop, Spark) is added advantage.- Certifications in AI/ML. (ref:hirist.tech)