Remote Linguistc AI & ML Engineer

Description:

• The Machine Learning Engineer – Generative AI & NLP Specialist will design, develop, and implement cutting-edge AI-driven systems with a strong focus on linguistics and language technology.
• This role will enhance translation systems using advanced Natural Language Processing (NLP) techniques and Generative AI (GenAI).
• The ideal candidate will have extensive experience in computational linguistics, machine translation (MT), and multilingual AI models, alongside expertise in end-to-end machine learning (ML) lifecycles, large language models (LLMs), and scalable AI solutions.
• Key responsibilities include designing and optimizing translation systems leveraging advanced NLP, Generative AI (GenAI), and linguistic expertise.
• The candidate will apply linguistic principles and computational linguistics techniques to enhance model performance, particularly in multilingual and domain-specific contexts.
• They will ensure contextual accuracy and linguistic coherence in AI-driven translation models and improve performance using linguistic quality metrics like BLEU, TER, METEOR, and human evaluation benchmarks.
• The role involves taking ownership of the entire machine learning pipeline, from prototyping and concept validation to scalable production deployment.
• Collaboration with linguists, translators, and domain experts to refine AI models for specific industry applications is essential.
• The candidate will implement monitoring frameworks to track linguistic model performance, detect anomalies, and ensure translation reliability.
• Automating pipelines for model retraining, fine-tuning, and adaptation to handle language evolution and domain-specific needs is also a key responsibility.
• They will deploy highly scalable multilingual inference endpoints, ensuring low-latency and high-accuracy responses.
• Ensuring compliance with data security, linguistic data privacy, and ethical AI standards is crucial.
• The candidate will develop well-documented APIs to enable seamless integration of GenAI-powered linguistic models into applications and external systems.
• They will optimize data retrieval and adaptation for multilingual NLP models, evaluating Retrieval-Augmented Generation (RAG) metrics such as precision and relevance.

Requirements:

• A background in computational linguistics, natural language processing (NLP), or language technology is required.
• The candidate must have a deep understanding of the full ML lifecycle, including development, training, deployment, and maintenance.
• Experience working with machine translation (MT), speech-to-text, text-to-speech, and multilingual AI models is necessary.
• Strong Python programming skills are essential, with expertise in ML libraries such as LangChain, LlamaIndex, PyTorch, TensorFlow, NumPy, SciPy, pandas, and scikit-learn.
• Proficiency in linguistic annotation, tokenization, stemming, lemmatization, and text normalization techniques is required.
• Hands-on experience working with BLEU, METEOR, TER, and other linguistic quality metrics to evaluate translation accuracy is necessary.
• Experience designing APIs for multilingual NLP applications with industry best practices is required.
• The candidate must have strong knowledge of large language models (LLMs), including open-source and commercial implementations, and their linguistic applications.
• Familiarity with vector and graph databases to support multilingual Retrieval-Augmented Generation (RAG) systems is necessary.
• Proficiency in cloud platforms, preferably Google Cloud Platform (GCP), is required.
• Experience with Docker, containerization, and deployment of AI-powered linguistic models is essential.
• The candidate must have a proven ability to ensure that GenAI deployments are scalable, secure, and linguistically robust.

Benefits:

• The position offers the opportunity to work on cutting-edge AI-driven systems with a focus on linguistics and language technology.
• The role allows for remote work, providing flexibility in the work environment.
• The candidate will have the chance to collaborate with experts in the field, enhancing their professional network and knowledge.
• There is potential for career growth and development within a rapidly evolving field of AI and NLP.
• The position includes the opportunity to work with advanced technologies and methodologies in machine learning and natural language processing.
• The role supports the development of innovative solutions that have a significant impact on translation systems and multilingual AI applications.