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Urgent! AmpsTek - Machine Learning Engineer - Artificial Intelligence Job Opening In Thiruvananthapuram – Now Hiring Ampstek

AmpsTek Machine Learning Engineer Artificial Intelligence



Job description

<p><p><b>Title :</b> Machine Learning Engineer.<br/><br/><b>Location :</b> Hyderabad/Trivandrum (India).<br/><br/><b>Job Type :</b> Contract.<br/><br/><b>Job Summary :</b><br/><br/><b>Position Summary :</b><br/><br/></p><p>We are seeking a dynamic Machine Learning Engineer focused on advancing our Predictive Modeling/Generative AI capabilities.

You will contribute to building scalable AI systems that impact real world Enterprise applications, while promoting responsible AI practices and collaborating across teams to accelerate innovation.<br/><br/><b>In this position you will :</b><br/><br/></p><p>- Design and implement machine learning models for anomaly detection in time series and behavioral data.<br/><br/></p><p>- Develop and maintain NLP pipelines for document processing and content generation.<br/><br/></p><p>- Preprocess and clean structured and unstructured data using standard techniques.<br/><br/></p><p>- Implement vectorization techniques and integrate with vector databases (e.g., FAISS, Pinecone, MongoDB Atlas Vector).<br/><br/></p><p>- Work with embedding models (e.g., OpenAI, Hugging Face) to support semantic search and retrieval tasks.<br/><br/></p><p>- Fine-tune and evaluate LLMs for specific use cases such as summarization, classification, and test case generation.<br/><br/></p><p>- Collaborate with backend engineers to expose ML models via APIs.<br/><br/></p><p>- Monitor model performance using metrics like precision, recall, F1 score, and ROC-AUC.<br/><br/></p><p>- Contribute to proof-of-concept projects involving GenAI and RAG architectures.<br/><br/></p><p>- Follow Responsible AI practices in model development and deployment.<br/><br/><b>Required Qualifications :</b><br/><br/></p><p>- 4+ years of experience in machine learning or data science roles.<br/><br/></p><p>- Proficiency in Python and common ML/NLP libraries (e.g., scikit-learn, spaCy, Hugging Face Transformers).<br/><br/></p><p>- Hands-on experience with anomaly detection techniques such as Isolation Forest, One-Class SVM, Autoencoders, or statistical methods is a plus.<br/><br/></p><p>- Familiarity with NLP tasks such as classification, summarization, and named entity recognition.<br/><br/></p><p>- Experience with vectorization techniques (TF-IDF, Word2Vec, BERT, etc.).<br/><br/></p><p>- Experience with vector databases (e.g., FAISS, Pinecone, ChromaDB) is a plus.<br/><br/></p><p>- Exposure to LLMs and prompt engineering.<br/><br/></p><p>- Basic understanding of MLOps concepts and model deployment practices.</p><br/></p> (ref:hirist.tech)


Required Skill Profession

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