Linguistc AI & ML Engineer

Overview: - Role focused on designing, developing, and implementing AI-driven systems with a specialization in Generative AI (GenAI) and Natural Language Processing (NLP). - Enhancement of translation systems using advanced NLP and GenAI techniques. - Application of computational linguistics and multilingual AI models. Key Responsibilities: - Design and optimize translation systems with NLP and GenAI. - Apply linguistic principles to improve model performance. - Own the machine learning pipeline from prototyping to production. - Collaborate with domain experts to refine AI models. - Implement monitoring frameworks for linguistic model performance. - Automate model retraining and adaptation processes. - Deploy scalable multilingual inference endpoints. - Ensure compliance with data security and ethical AI standards. - Develop APIs for GenAI-powered linguistic models integration. - Optimize data retrieval for multilingual NLP models. Requirements/Skills/Qualifications: - Background in computational linguistics, NLP, or language technology. - Deep understanding of the ML lifecycle. - Experience with machine translation, speech-to-text, text-to-speech, and multilingual AI models. - Strong Python programming skills and expertise in ML libraries. - Proficiency in linguistic annotation and tokenization techniques. - Experience with BLEU, METEOR, TER, and linguistic quality metrics. - Knowledge of large language models and vector/graph databases. - Familiarity with cloud platforms, Docker, and containerization. - Proven ability to ensure scalable, secure, and robust GenAI deployments. Compensation & Benefits: - The job description does not provide specific details on compensation and benefits. (Note: The compensation and benefits section is intentionally left blank as per the instruction to omit such details.)