The Applied Scientist will:
- Finetune and integrate the latest Large Language Models (LLMs) such as OpenAI/Gemini/Claude/Llama/MistralAI models into production systems.
- Train, finetune and deploy large-scale NLP and CV models to power complex document understanding experiences.
- Design and implement scalable, efficient and highly precise QA RAG frameworks
- Work with complex datasets from various sources to build Extract, Transform, and Load (ETL) data pipelines for downstream tasks
- Collaborate with other product managers and engineers in the team to build tools to evaluate and improve the end-to-end AI quality of our production systems.
- Effectively communicate and demonstrate work to stakeholders
- Lead projects from end to end, take full ownership, and make key decisions about architecture, modeling approaches, and tools.
- Align technical work with business goals and communicate the impact of machine learning models in terms of business outcomes.
Qualifications:
- Bachelor's, Master’s OR PhD degree in Computer Science, Electrical or Computer Engineering, or related field (e.g., statistics, predictive analytics, research)
- Experience building sophisticated RAG pipelines with LLMs (with frameworks like LangChain, LlamaIndex, Hamilton, etc.)
- Experience working on deep learning architectures specifically with Natural language-based models (Pytorch/Tensorflow), vector databases and graph databases
- Experience developing applications using prompt engineering, fine tuning, Google Vertex AI APIs, Azure Open AI APIs or equivalent.
Preferred Qualifications:
- Bachelor’s degree in Computer Science, Electrical or Computer Engineering, or related field (e.g., statistics, predictive analytics, research) AND 7+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master’s/PhD degree in Computer Science, Electrical or Computer Engineering, or related field (e.g., statistics, predictive analytics, research) AND 5+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers)
- 3+ years experience writing production code as well as deploying and maintaining shipped AI/ML models over time
- 2+ years experience conducting research as part of a research program (in academic or industry settings) in areas of machine learning, deep learning, NLP, data mining, information retrieval
- 5+ years of experience in Python