Machine learning engineer in forecasting

ENERLATTICE; United States; Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

Health coverage

Annual wellbeing budget

Equipment stipend

Flexible time off

Job summary

EnerLattice seeks a senior ML engineer to improve forecast accuracy for solar and grid forecasting, publishing uncertainty bands, and ensuring a strict boundary between model advice and settlement authority. Join a remote-friendly AI team with Berlin, Singapore, Austin, London, and Tokyo hubs.

The role emphasizes productionizing forecasting models with monitoring and rollback plans, collaborating with plant and settlement stakeholders, and contributing to a practical, scalable energy forecasting

Qualifications

• Staff-level ML experience with time-series or forecasting systems.
• Ability to productionize models with monitoring and rollback plans.
• Clear communication with plant and settlement stakeholders.
• Experience in energy markets, renewables, or grid forecasting is a plus.

Responsibilities

• Improve forecast accuracy and published error bands.
• Ship model updates that operators can trust in daily planning.
• Keep a hard boundary between advice and settlement authority.

Skills

Time-series forecasting

Model deployment & monitoring

Stakeholder communication

Education

MS in ML/CS or related field

Tools

Model monitoring tools

CI/CD for ML deployment

Forecasting platforms

Job description

Описание

You will improve forecast accuracy and published error bands while keeping a hard boundary between advice and settlement authority.

Задачи

• Improve forecast accuracy and published error bands.
• Ship model updates that operators can trust in daily planning.
• Keep a hard boundary between advice and settlement authority.

Требования

Staff-level ML experience with time-series or forecasting systems. Ability to productionize models with monitoring and rollback plans. Clear communication with plant and settlement stakeholders. Будет плюсом: Experience in energy markets, renewables, or grid forecasting; Background publishing uncertainty / error-band calibrated models; Familiarity with operator tooling and human-in-the-loop workflows

Условия

Forecasts that operators use every interval—not offline research only. Clear separation between model advice and settlement authority.

Berlin hub option with a remote-friendly AI team.

Competitive salary with meaningful equity

Remote-first collaboration with hubs in Berlin, Singapore, Austin, London, and Tokyo.

Health coverage plus an annual wellbeing budget Equipment stipend and flexible time off Work on a real solar plant and the settlement network around it