We have a big vision which is why we need you—an innovator and problem solver ready to revolutionize and empower businesses to succeed.
Job Overview
As a Machine Learning Engineer at Scorpion, you’ll work with our growing data science team to develop data products for Scorpion and its clients. We’re looking for a highly skilled Python developer excited to iterate on proofs of concept/development models produced by our data science team to improve resilience, performance, and accuracy in the production environment. Your work will improve the team’s ability to rapidly iterate and operationalize models, and protect deployments against model drift, data quality, and programming errors.
As a generalist rather than a specialist, your success will rely on a broad base of knowledge spanning web application engineering (microservices, REST APIs), DevOps (CI / CD deployment pipelines, test-driven development), infrastructure (Kubernetes, cloud), and data science (Python and familiarity with cloud machine learning environments such as Azure ML or Amazon SageMaker).
What You'll Do
Responsibilities:
- Develop CI/ CD pipelines to reduce errors in the deployment of new or updated models without impairing each data scientists’ ability to rapidly experiment.
- Improve scalability and performance of deployed models by refactoring Python code or tuning inference clusters.
- Improve model reproducibility and facilitate collaboration amongst data scientists by enabling data version control and feature stores.
- Analyze and monitor the performance of production models to protect against degradation or drift.
- Enable resilient model deployment architectures such as champion-challenger.
- Support data scientists in algorithm selection, hyperparameter tuning, and code review.
What You'll Need
Qualifications:
- 3+ years of Python development experience, ideally with some exposure to full-stack application engineering as well as data science.
- Experience operationalizing external-facing models in a cloud machine learning environment (Azure ML preferred), enabling highly performant batch and live inference.
- Extensive industry modeling experience (degree in Computer Science/ Statistics/ Data Science/ Machine Learning/ etc. and one prior role as a machine learning engineer or applied data scientist).
- Python Expertise (including extensive experience with pandas/numpy/scikit-learn/xgboost/etc.) and understanding of common machine learning algorithms (RF, SVM, LR, GBDT, GLMs, etc.) as well as probabilistic modeling.
- Familiarity with Test-Driven Development and modern CI / CD best practices
- Preferred: Knowledge of Marketing or small business domain.
- Preferred: Experience in a fast-paced SaaS startup development environment