Machine Learning Engineer

2 months ago

H1B sponsor

Base Salary

$180k - $230k/yr

Responsibilities

Build and own scalable, reliable, and reproducible training infrastructure for underwriting models using very large patient and claims datasets.
Build and own the API serving layer that produces real-time quotes in seconds.
Own the latency, reliability, and scalability of the production serving path used by the quoting product.
Develop tooling that enables data scientists and actuaries to test features and ideas more efficiently.
Build backtesting and validation infrastructure for rapid and trustworthy model evaluation.
Reduce friction between experimentation and validated, production-ready models.
Operate and maintain reliable production infrastructure, including monitoring and on-call support.

Strong production track record building ML or data infrastructure at scale.
Deep proficiency in Python and experience processing large datasets with Spark, Databricks, or an equivalent tool.
Experience with production model training pipelines and/or low-latency model serving.
Experience building tooling for feature testing, experiment tracking, backtesting, or similar developer- and researcher-facing infrastructure.
Ability to own systems end-to-end, establish standards, and operate reliable production infrastructure with SLAs, monitoring, and on-call responsibilities.
Genuine interest in working directly with modeling and data science.
Prior experience in healthcare, insurance, or another regulated industry is preferred.
Experience with MLOps tooling such as MLflow, feature stores, experimentation platforms, or production support for data science or actuarial teams is preferred.