YASH Technologies - Lead Data Scientist - Artificial Intelligence/Machine Learning

<p><p><b>Key Responsibilities :</b></p><p><p><b><br/></b></p>- Lead the end-to-end delivery of Machine Learning (ML) and Generative AI (GenAI) use cases from conceptualization through deployment.<br/><br/></p><p>- Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance enterprise AI capabilities.<br/><br/></p><p>- Build and optimize scalable, reusable GenAI accelerators suitable for diverse business needs.<br/><br/></p><p>- Collaborate with solution architects, presales teams, and cross-functional stakeholders to align AI solutions with business goals.<br/><br/></p><p>- Ensure best practices in software development, including modular code design, rigorous testing, and governance compliance.<br/><br/></p><p>- Monitor and optimize AI models for security, performance, and cost efficiency on cloud Skills & Qualifications : </b></p><p><br/></p><p>- 8 to 10 years of relevant experience in Machine Learning and Generative AI development and deployment.</p><p><br/></p>- Hands-on experience with LangChain, LangGraph, embedding techniques, and prompt engineering.<br/><br/></p><p>- Strong expertise in classical machine learning algorithms including XGBoost, Random Forest, and time-series forecasting.<br/><br/></p><p>- Proficiency with Python ML ecosystem (e.g., scikit-learn, pandas, NumPy) and building RESTful APIs using FastAPI.<br/><br/></p><p>- Deep understanding of cloud optimization techniques and AI security best practices.<br/><br/></p><p>- Experience in architecting large-scale AI pipelines and accelerators.<br/><br/></p><p>- Ability to work collaboratively in cross-functional teams including architects and presales Qualifications : </b></p><p><br/></p><p>- Experience with cloud platforms such as AWS, Azure, or GCP.</p><p><br/></p>- Familiarity with containerization and orchestration tools like Docker and Kubernetes.<br/><br/></p><p>- Knowledge of MLOps practices and CI/CD pipelines for ML models.</p><br/></p> (ref:hirist.tech)