.Our client is seeking a highly skilled NLP Engineer specializing in Large Language Models (LLMs) to join their AI Research and Development team. The ideal candidate will have a strong background in machine learning, natural language processing, and experience working with large-scale language models like GPT, Claude, Llama, or Bard.As an NLP Engineer in their AI Labs, you will be responsible for bringing the latest innovations in ML research to the company. The mission of the department is to discover, architect, design, and refine solutions for the fields of Drug Discovery, Clinical Trials, Factory Automation, Medical Research, among others.Your focus will be on building solutions in Natural Language Processing (NLP), Deep Learning and Analytics, from gaining data and business understanding through data preparation and modelling, model evaluation to the result presentation and the solution deployment. In your role, you will apply a variety of models on large-scale datasets to... address various business problems using advanced techniques. You will write high-quality production code, build and maintain robust, scalable data pipelines, document and validate the approach, set up processes to monitor, operate and continually improve the efficiency and performance of the implemented solutions.Specific Responsibilities:Design, develop, and maintain NLP models.Review papers and keep the team up to date with SotA LLM algorithms and techniques.Collaborate with cross-functional teams across the company to integrate LLMs into various business units and applications.Optimize your models for performance, scalability, and efficiency.Stay up to date with the latest developments in Deep Learning.Analyze and interpret complex datasets to define and improve model accuracy.Write clean, maintainable, and efficient code.Provide technical guidance and mentorship to other data scientists specialized in other domains.Graduated with a higher degree in computer science, information technology, data science, or similar fields.Proven experience in developing and deploying machine learning models, particularly in natural language processing.Strong proficiency in Python, and experience with machine learning frameworks such as PyTorch, Hugging Face, or Pandas.Good understanding of document indexing systems and vector databases (e.G. Qdrant, Langchain)Experience in agile software development, version control (git), CI/CD, and containers (Docker, Kubernetes)Knowledge of microservices, RESTful APIs, Dockers and AWS Container Services is a plusGeneral expertise within most of the following areas: supervised learning, unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, and Bayesian statisticsExperience writing clean code and deploying models in production
