ML/NLP Engineer — dMetrics

ML/NLP Engineer — dMetrics Back to the list ML/NLP Engineer You are interested in challenging NLP problems like text classification, entity recognition and disambiguation and relation extraction. We expect you to work closely with researchers and engineers, provide leadership, code with discipline and design meaningful experiments. You are comfortable with working on very large (and noisy) datasets, curating and enriching knowledge bases and packaging your model artifacts. You understand the importance of evaluation metrics and understand when to optimize, and for what. You will use your programming skills and experience working with popular ML/DL libraries (e.g., spaCy, Hugging Face, PyTorch, ONNX) to build and deliver models that bring value to our clients and can run efficiently over millions of large documents in reasonable time without breaking the bank. You keep up with the latest tools, frameworks and libraries, enjoy experimenting with them, and understand when they should and shouldn’t be adopted for our use cases and tasks. You are comfortable with change. You’ve had positive experience working for a startup before. You will work on Improving Entity Recognition and Entity Linking using User Feedback, Dense Embeddings, Knowledge Graph Representations Improving Document Retrieval and Search Required Skills 2+ years of experience in prototyping, evaluating, and deploying production NLP systems Bonus: work on text classification, entity recognition, entity disambiguation, relation extraction, or knowledge base construction Big plus: Experience with Graph ML Experience with tools for prototyping and deploying deep learning models (scikit-learn, PyTorch, TensorFlow, spaCy, Hugging Face, ONNX, etc.) Fluency in state-of-the-art deep learning and NLP methods (CNNs, RNNs, Transformers, pre-training, fine-tuning, transfer learning, attention, ontologies, etc.) Strong understanding of computer science fundamentals (algorithms, data structure