ML Time Series Forecasting Engineer (Remote)

North.Cloud; New York (NY); Hybrid; USD 192,000 - 257,000; Full time

Benefits offered by this job

Unlimited PTO

Parental leave (16 weeks)

Company breaks

Health insurance

Dental and vision

FSA

Sabbatical

Job summary

North.Cloud is hiring a Software Engineer, ML (Time Series Forecasting) in a hybrid role based in New York City with an office in Dumbo, Brooklyn; remote US option is also available. You will own the models behind North's internal forecasting service, shaping training, evaluation, and production monitoring.

You will collaborate with data scientists and cross‑functional teams to deliver accurate forecasts, improve backtesting, and build a reliable shared service.

Qualifications

• 4+ years of software or ML engineering experience.
• Experience shipping time series models to production.
• Strong Python and SQL skills.
• Experience with model monitoring, drift, and retraining.
• Ability to explain model behavior to non-engineers.
• Experience collaborating with data scientists and other teams.

Responsibilities

• Build and improve time series models for forecasts across diverse customers.
• Deploy models as a reliable shared service with clear interfaces.
• Design forecasting service architecture including training, versioning, evaluation, and serving.
• Improve evaluation, backtesting, and monitoring of forecast accuracy.
• Develop detection for unusual forecasts and drift to surface issues.
• Quantify forecast uncertainty for downstream features.
• Collaborate with data scientists and other teams to translate forecast results into actionable insights.

Skills

Time series forecasting

Python

SQL

Production deployment

Collaboration with data scientists

AI tooling

Tools

AWS ML services

Job description

North.Cloud is hiring a Software Engineer, ML (Time Series Forecasting) in a hybrid role based in New York City with an office in Dumbo, Brooklyn; remote US option is also available. You will own the models behind North's internal forecasting service, shaping training, evaluation, and production monitoring.

You will collaborate with data scientists and cross‑functional teams to deliver accurate forecasts, improve backtesting, and build a reliable shared service.