Senior Staff Engineer – NLP
Company | Samsung Research America |
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Location | Mountain View, CA, USA |
Salary | $158800 – $218100 |
Type | Full-Time |
Degrees | Bachelor’s, Master’s, PhD |
Experience Level | Expert or higher |
Requirements
- BS/MS/PhD in NLP, ML, AI, Engineering or equivalent, or equivalent combination of education, training, and experience
- 12+ years of relevant professional experience in Deep Learning, Natural Language Understanding, Natural Language Generation, Open Domain Question Answering, Text Classification, Information Retrieval, Knowledge Extraction, Planning in AI, Commonsense Reasoning in AI
- 5+ Years of experience with building end-to-end systems based on machine learning or deep learning methods (ETL, modeling and deployment)
- Strong understanding of computer science fundamentals such as algorithms, data structures and run-time analysis
- Proficiency in Java and Python
- Experience with deep learning-based NLP models such as BERT, GPT, other transformers
- Experience with advanced deep learning-based coding models and Retrieval Augmented Generation
- Experience with traditional NLP tools such as BoW models, word embeddings, and Python NLP toolkits such as spacy, NLTK, huggingface
- Experience with machine learning techniques, tools, and frameworks like Keras, TensorFlow, pytorch
- Able to solve real–world problems using cutting–edge ideas and independent research
- A willingness to learn and remain agile in a dynamic environment
- Analytical and problem-solving skills for design, creation and testing of custom software
- Extensive experience with software prototyping or designing experimental software
- Adept at adapting academic ideas and theoretical algorithms into a production system
Responsibilities
- Research, prototype, develop, deploy and scale innovative Machine Learning/Deep Learning solutions in collaboration with Linguistic Experts and Product Management teams
- Develop predictive models on large-scale datasets to address various business problems leveraging advanced statistical modeling, machine learning, deep learning or data mining techniques
- Design and implement infrastructure for orchestrating end to end machine learning lifecycles
- Set up processes to monitor and continually improve efficiency and performance of KPIs
- Software development including algorithm implementation, optimization, performance profiling, integration to production systems, testing and documentation
- Write high-quality production code as you build and maintain robust, scalable machine learning systems
- Program primarily in Python and / or Java using efficient Software design principles
- Scale and improve performance of Natural Language systems in production
Preferred Qualifications
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No preferred qualifications provided.