Remote Machine Learning Engineer - NLP

Our client, a cutting-edge AI research and development company, is seeking a highly skilled Remote Machine Learning Engineer specializing in Natural Language Processing (NLP) to join their innovative team. This is a fully remote position, offering the opportunity to work on groundbreaking AI projects from anywhere in the US. You will be responsible for designing, developing, and deploying advanced NLP models and solutions that drive intelligent features in our client's products. The ideal candidate possesses a strong theoretical foundation in machine learning, deep expertise in NLP techniques (e.g., sentiment analysis, topic modeling, question answering, text generation), and hands-on experience with deep learning frameworks like TensorFlow or PyTorch. Responsibilities include data preprocessing, feature engineering, model training, evaluation, and optimization for large-scale text datasets. You will collaborate closely with data scientists, software engineers, and product managers to translate business requirements into effective ML solutions. This role demands strong programming skills in Python, proficiency with relevant libraries (e.g., Hugging Face Transformers, spaCy, NLTK), and experience with cloud platforms (AWS, Azure, GCP) for model deployment and scaling. The ideal candidate is passionate about pushing the boundaries of AI, stays current with the latest research in NLP and ML, and can contribute innovative ideas to the team. You will be involved in the entire ML lifecycle, from initial research and experimentation to production deployment and ongoing monitoring. This is a unique opportunity to work on challenging problems, contribute to state-of-the-art AI technologies, and have a significant impact in the field of artificial intelligence. Successful candidates are highly analytical, possess excellent problem-solving skills, and thrive in a collaborative, remote research environment. Your work will directly influence the intelligence and capabilities of our client's next-generation AI products. We are looking for individuals who are not afraid to tackle complex problems and deliver impactful solutions.

Responsibilities: Design, develop, and implement advanced NLP models and algorithms. Process, clean, and analyze large-scale text datasets for machine learning. Implement deep learning architectures for various NLP tasks (e.g., text classification, NER, summarization). Train, evaluate, and optimize ML models for performance and accuracy. Deploy ML models into production environments using cloud platforms. Collaborate with cross-functional teams to define ML project requirements and deliverables. Stay current with state-of-the-art research in NLP, ML, and deep learning. Write clean, efficient, and well-documented code in Python. Develop and maintain ML pipelines and workflows. Conduct experiments and analyze results to improve model performance. Contribute to the development of AI strategies and roadmaps. Mentor junior engineers and share knowledge within the team. Qualifications: Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. 4+ years of professional experience in Machine Learning Engineering, with a strong focus on NLP. Proven experience with NLP techniques such as sequence modeling, attention mechanisms, transformer networks, and language generation. Proficiency in Python and ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Hands-on experience with NLP libraries like Hugging Face Transformers, spaCy, or NLTK. Experience with cloud platforms (AWS, Azure, GCP) for ML model deployment and MLOps. Strong understanding of algorithms, data structures, and software engineering principles. Excellent problem-solving, analytical, and critical thinking skills. Ability to work effectively in a remote, collaborative team environment. Strong communication skills, with the ability to explain complex technical concepts clearly. This role is a fully remote position open to candidates across the US, focusing on advancing the frontiers of AI and NLP.