About this role
- Work closely with team of data scientists to design, build, and test machine learning models to solve complex business challenges.
- Researching & implementing state of the art modeling approaches including but not limited to zero-shot/few-shot learning, embedding techniques, fine-tuning etc.
- Ensure high quality code that meets business objectives, quality standards and secure web development guidelines.
- Building reusable tools to streamline the modeling pipeline and sharing knowledge.
- Manage project stakeholder expectations and issue communications on progress.
- React to shifting priorities without compromising deadlines and momentum.
Minimum Requirements and Qualifications
- Must have:
8+ years’ experience in Machine Learning (ML), with deep expertise in writing, and reviewing production code in Python.
- Experience with LLM tooling and frameworks like LangChain, LlamaIndex etc.
- Knowledge of basic algorithms, object-oriented and functional design principles, and best-practice patterns
- Experience with designing scalable end-to-end Machine Learning/NLP systems.
- Experience on distributed, high throughput and low latency architecture.
- Understanding of NLP techniques around text cleaning/pre-processing, entity extraction, encoder-decoder architectures, similarity matching etc.
- Experience building software on top of containerization technology (Kubernetes, Docker etc.), and familiarity with frameworks/tools such as FastAPI, Uvicorn.
- Familiarity with Continuous Integration tools such as Jenkins.
- Nice to have:
Experience defining system architectures and exploring technical feasibility trade-offs is a huge plus.
- Experience in NLP feature engineering and SoTA modeling techniques, such as transformers (e.g., BERT , GPT) is a huge plus.
Familiarity with end-to-end application development using full stack is a plus.
- Experience in P&C insurance is a plus