Software Engineer, ML (Time Series Forecasting)

North Cloud; New York (NY); Hybrid; USD 186,000 - 257,000; Full time

Benefits offered by this job

Unlimited PTO

16 weeks parental leave (birthing 4 w/

Two company-wide breaks

Aetna Medical plan

Dental and vision insurance

FSA

Sabbatical after 4 years

Job summary

North Cloud is hiring a Software Engineer, ML (Time Series Forecasting) to own models behind forecasting across the platform. You will train, evaluate, deploy, and monitor models, working with data scientists and feature teams to ensure forecast quality and actionable results for customers.

The role emphasizes shipping models to production, monitoring drift, and collaborating with Services, Commitments, and Data teams.

Qualifications

• 4+ years of software or ML engineering; shipped time series models to production and owned post-launch.

Responsibilities

• Build and improve time series models for forecasted spend and budgets across diverse usage patterns.

Skills

Python

SQL

Time series forecasting

Production deployment

Model monitoring

Drift detection

Cross-functional collaboration

Tools

AWS ML services

Job description

Software Engineer, ML (Time Series Forecasting)

About North Cloud

The public cloud is rapidly evolving, with businesses investing over $200 billion annually in cloud technology. As AI accelerates demand for scalable infrastructure, cloud costs are soaring, and most teams still rely on spreadsheets to manage them.

At North, we're building the next-generation cloud, AI, and data spend management platform. We give companies real-time visibility, control, and automation over their digital asset finances so they can grow efficiently without wasting time or money.

Backed by top-tier investors and trusted by companies managing complex cloud environments, North is building the financial operating system for the public cloud.

About the Role

Forecasting sits underneath much of North: projected spend, budgets, and the commitment purchases we make on customers' behalf all depend on knowing where a customer's usage is headed. When a forecast is off, customers feel it, either in missed savings or in commitments that go unused.

You'll join the Services team and own the models behind North's internal forecasting service, working with your teammates on the service that delivers forecasts across North's features. You'll shape how the service evolves, from how models are trained and evaluated to how forecast quality is monitored in production. You'll also work closely with data scientists and the teams who rely on forecasts, so results are clear to the people making decisions from them.

We're hiring for this role without a fixed level. We'll level you based on experience and on how you work, using our engineering ladder.

What You'll Do

• Build and improve the time series models behind projected spend, budgets, and commitment recommendations, across customers with very different sizes and usage patterns.
• Partner with your Services teammates to take models into production as a reliable shared service with clear interfaces.
• Shape the forecasting service's architecture, including how models are trained, versioned, evaluated, and served.
• Improve how we evaluate, backtest, and monitor forecast accuracy over time.
• Build proactive detection and alerting for unusual forecasts and model drift, so issues surface before they affect a decision.
• Quantify forecast uncertainty, such as with prediction intervals, so the features that use forecasts can account for it.
• Work with data scientists to turn forecast results and model changes into findings product and business teams can act on.
• Work with the Commitments, Visibility, and Data teams on what each feature needs from a forecast.

What We're Looking For

• 4+ years of software or machine learning engineering experience, including shipping time series models to production and owning them after launch.
• Deep experience with time series forecasting across classical statistical methods and machine learning approaches, and judgment about when each fits.
• Experience with time-aware validation, backtesting, and forecast accuracy metrics, and an understanding of their tradeoffs.
• Experience monitoring production models, including drift, anomaly detection, and retraining.
• Fluency in Python and SQL, and experience with large datasets.
• Experience collaborating with data scientists, and explaining model behavior and uncertainty to people outside engineering.
• Pragmatic, informed use of AI coding tools.

Nice to Have

• Experience working as a data scientist, or doing analysis work alongside ML engineering.
• Experience with probabilistic forecasting.
• Experience forecasting usage, demand, or spend across many accounts with different patterns.
• Experience with cloud usage, billing, or pricing data.
• Experience with AWS ML services.
• Familiarity with FinOps concepts.

Work Setup

Hybrid role based in New York City, with an office in Dumbo, Brooklyn

Team members typically work in the office 2-3 days per week

OR Remote US

• Unlimited PTO
• 16 weeks of paid parental leave (birthing parents receive an additional 4 weeks at 50% pay)
• Two company-wide breaks per year: one around Labor Day and one at the end of the year
• Aetna Medical plan with the majority of the premium covered by North
• Dental and vision insurance
• Flexible spending account (FSA) for health expenses and commuter benefits
• 30 day sabbatical every 4 years

The pay range for this role is:

192,000 - 257,000 USD per year (Brooklyn HQ)

186,000 - 240,000 USD per year (US Remote)