Engineering Manager Associate

Associate Principal Engineer, Data ScienceJob DescriptionREQUIREMENTS : - Total experience 11+ years.- Hands on working experience in data science with a focus on predictive modeling and optimization.- Should have strong experience with Python (and/or R) and libraries such as Pandas, NumPy, Scikit-learn.- Should have strong knowledge of Cloud Architecture and deployment of data solutions in cloud ecosystems (e.g. Azure, GCP).- Must have hands on experience with SQL relational databases, and big data ecosystems- Should have proven expertise in machine learning, mathematical optimization (e.g., LP, IP, genetic algorithms, RL), and NLP techniques.- Must have familiarity with Generative AI fundamentals and hands-on experience with RAG, Lang Chain, Llama Index, and prompt engineering.- Must have strong understanding of MLOps principles and tools for CI/CD, monitoring, and model lifecycle management.- Should have excellent communication skills and the ability to collaborate effectively with cross-functional teams.RESPONSIBILITIES : - Writing and reviewing great quality code- Understanding the client's business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.- Mapping decisions with requirements and be able to translate the same to developers.- Identifying different solutions and being able to narrow down the best option that meets the clients' requirements.- Defining guidelines and benchmarks for NFR considerations during project implementation.- Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers.- Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.- Developing and designing the overall solution for defined functional and non- Functional requirements; and defining technologies, patterns, and frameworks to materialize it.- Understanding and relating technology integration scenarios and applying these learnings in projects.- Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.- Carrying out POCs to make sure that suggested design/technologies meet the requirements. (ref:hirist.tech)