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Primary skills:Technology->AI-Data science->Machine Learning,Technology->AI-Generative AI->Generative AI for Data Analytics,Technology->OpenSystem->Python - OpenSystem->Python
Key Responsibilities:
Develop and maintain Python-based ML/GenAI components for NLP use cases, from prototyping to production-ready implementations.
Build and fine-tune models using PyTorch, focusing on accuracy, latency, and resource efficiency.
Design data preprocessing and feature engineering workflows for text datasets, ensuring quality and reproducibility.
Implement evaluation strategies for NLP/GenAI outputs, track metrics, and iterate based on measurable results.
Collaborate with cross-functional teams to translate requirements into model/system designs and deliverables.
Troubleshoot model and pipeline issues, perform root-cause analysis, and improve system reliability.
Write clean, maintainable code with appropriate documentation, tests, and version control practices. Minimum Qualifications:
Bachelor’s/Master’s degree (or equivalent) in Engineering/Computer Science or related field (BE/BTech/MSc/MCA/MTech).
2–3 years of hands-on experience building ML solutions using Python.
Practical experience with NLP concepts and workflows (tokenization, embeddings, text classification, sequence modeling).
Working knowledge of PyTorch for training, fine-tuning, and inference.
Strong problem-solving skills and ability to collaborate effectively with engineering and data stakeholders. Preferred Qualifications:
Experience with transformer-based NLP/GenAI approaches (fine-tuning, prompt-based workflows, evaluation techniques).
Exposure to MLOps practices such as experiment tracking, model versioning, and reproducible training pipelines.
Familiarity with deploying ML models as services and optimizing inference performance.
Experience working with modern data/ML tooling for dataset handling, training acceleration, and scalable experimentation.
Demonstrated ability to communicate trade-offs and results clearly to technical and non-technical stakeholders. Good to have skills: Hugging Face Transformers, LangChain, Vector Databases (FAISS/Pinecone), MLflow, Docker
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