Description:
This role will be part of our Artificial Intelligent Team (TRAIT) and will be responsible for
providing key Machine Learning deliverables to our global user base.
Responsibilities include, but are not limited to:
- Constructing machine learning models, including data collection, normalization, and standardization, data pipeline construction, model selection, and hyperparameter tuning, working ML systems that can add new data to an ML model.
- Working on and researching the most recent LLM and GenAI models, safety, interpretability, and applications.
- Creating apps to present ML models and host them in the cloud or locally.
- Creating pipelines to query, retrieve, and update data for existing applications to keep them updated.
- Supervising the scaling and management of the machine learning modeling ecosystem.
- Finding orthogonal data sets to supplement models and increase alpha.
- Staying abreast of new technology and machine learning methodologies and implementing them into the model-building architecture.
- Working alongside (re)insurance domain experts to improve predictive aspects of their lines of business.
Requirements:
As an ideal candidate, you will possess the following skills and knowledge:
- Proven track record of building, scaling, and productizing multiple machine learning models
- Minimum of 5 - 7 years of full lifecycle ML projects from research to production and post-production modifications.
- Ideally looking for someone with 8-10 + years of total career experience in engineering
- 4+ years of Property & Casualty industry experience .
- Strong experience in the full life-cycle of machine learning models from initial theorizing to final implementation & support.
- High proficiency with working with LLMs- fine-tuning, RLHF, distillation, optimization
- Experience working with sparse, high-dimensional, tabular, and time series data
- Python ML stack
- PyTorch, TensorFlow, CUDA
- Boosting and bagging algorithms
- ML Optimization Techniques
- Ensemble Stacking and Meta Learners
