Apply statistical and machine learning techniques to process and analyze unstructured textual data
Develop and fine-tune machine learning models for tasks such as entity recognition, classification, and text generation
Utilize pre-trained language models (e.g. GPT, LLAMA) and adapt them for specific use cases
Optimize the models for production usage, including considerations for scalability, latency, and resource
Monitor and refine deployed models for performance and efficiency, and conduct troubleshooting when necessary
Work closely with interdisciplinary teams to deliver high-quality features and solutions
Stay current with advancements in NLP research, methodologies, and best practices
Be consistently productive and operate with a high degree of autonomy
Requirements & Skills:
A bachelor’s degree in Statistics, Computer Science, related technical field, or equivalent practical experience
A minimum of 6 years of experience in a quantitative role, with ideally much of that as a machine learning engineer or a data scientist
Knowledge of and expertise in Natural Language Processing (NLP)
Proficiency in a data query language (e.g. SQL), and a programming language (e.g. Python)
Demonstrable experience with the full lifecycle of machine learning models – from development to deployment and monitoring
Being an excellent team player with a proven ability to work effectively in cross-functional teams, showing a high degree of collaboration, flexibility, and respect for diverse perspectives
An ability to be self-directed after work is assigned and help less experienced team members to get unblocked
