The company is looking to scale its AI-powered scheduling and forecasting solutions by designing, training, deploying, and monitoring machine learning models that address real-world customer needs.
Requirements
- 4+ years’ experience with Python and ML frameworks.
- 1+ year of experience with MLOps and maintaining ML models at scale.
- Strong knowledge and hands-on experience with: Python programming
- SQL and relational databases; ETL processes
- Cloud technologies (AWS, GCP, or Azure)
- Git or other version control systems
- Model versioning/tracking (DVC, MLFlow)
Responsibilities
- Build and test machine learning models to support their platform.
- Design, build, and deploy data and ML pipelines on AWS.
- Enable an iterative lifecycle for data products to improve, integrate, and deploy.
- Standardize workflows, analysis, and modeling for deployment and observability in production.
- Develop monitoring and observability systems for ML models and experiments.
- Collaborate across teams to align modeling with engineering standards.
Other
- Hybrid - 2 days onsite
- 2–4 years of relevant experience.
- Bachelor’s or Master’s degree in a quantitative field.
