Job Description : About the Job :
- Design, code, test, debug, and document software in compliance with client standards, policies, and procedures.
- Analyze business needs and create effective software solutions.
- Prepare design documentation and develop test data for unit, string, and parallel testing.
- Evaluate and recommend software and hardware solutions to meet business requirements.
- Troubleshoot and resolve customer issues with software solutions while implementing improvements and enhancements.
- Collaborate with business and development teams to clarify requirements and ensure testability.
- Draft, revise, and maintain test plans, test cases, and automated test scripts.
- Execute test procedures, log defects, recommend corrective actions, and retest to confirm resolution.
- Document testing procedures for repeatability and knowledge sharing.
- Conduct performance and scalability testing as needed.
Essential Job Functions :
Lead small to moderately scoped projects, including supervision of junior team members when required.Provide solutions to a diverse range of complex technical challenges.Manage schedules, costs, and documentation to drive projects to successful completion.Mentor, assign, and review the work of less experienced developers.Perform estimation efforts and track progress for assigned projects.Draft and execute test plans / scripts with a focus on end-to-end system flows.Perform root cause analysis of defects, define corrective actions, and communicate results effectively.Qualifications :
Essential Requirements :
Proficiency in Python 3.x.Basic understanding of Natural Language Processing (NLP).Experience designing and building NLP models such as Text Classifiers, Recommenders, and Conversational Agents.Familiarity with Embeddings and Vector Databases.Understanding of Language Models.Experience with GenAI frameworks (e.g., Retrieval Augmented Generation - RAG).Experience designing and building inference APIs using Python frameworks like FastAPI, Flask, or Django.Experience with Relational and Non-Relational Databases.Knowledge of LLMOps stacks such as LangChain or LlamaIndex.Good to Have
Hands-on experience with fine-tuning LLMs, deployments, and MLOps.Deep understanding of Python development stack, ecosystems, and libraries :NLTK, RASA, LangChain, NumPy, SciPy, Pandas, Dask, spaCy, scikit-learn, PyTorch, TensorFlow.Experience in GenAI model evaluation, fine-tuning, and deployments.Familiarity with Python testing frameworks (e.g., Pytest, unittest).(ref : hirist.tech)