Senior/Staff AI/ML Engineer, Plant Intelligence

1stavenuepower; United States; Remote; USD 237,000 - 258,000; Full time

Benefits offered by this job

Equity

Health coverage

Retirement match

Job summary

1stavenuepower seeks an experienced software engineer to build production ML capabilities for solar and battery plant modelling and operation. You will own models from prototypes through deployment and monitoring, blending physics with data-driven approaches.

The role emphasizes building datasets, scalable pipelines, and robust deployment workflows. The team values strong Python/SQL skills, data engineering experience, and familiarity with data lakes, streaming data, and IaC tools like

Qualifications

• 6+ years in software engineering with at least 3 years building ML systems for production.
• Strong Python and SQL skills and practical experience with current ML libraries.
• Data engineering experience building dependable pipelines for high-volume sensor or time-series data.
• Familiarity with model training and evaluation workflows, registries, and production monitoring.
• Experience with data lakes, streaming systems, and workflow orchestration.
• Infrastructure-as-code experience, such as Terraform, plus a track record of owning work from prototype to production.

Responsibilities

• Develop predictive models that combine physical understanding of plant behavior with machine learning.
• Create and maintain labeled datasets from operations, maintenance, and field information.
• Build repeatable workflows for model training, evaluation, and deployment.
• Package models for site use and coordinate with infrastructure engineers on deployment.
• Monitor model performance and use observed results to guide improvements.

Skills

Python

SQL

Production ML systems

Data pipelines

Data lakes / streaming

Infrastructure as Code

Tools

Terraform

Job description

Role overview

Build the first production machine learning capabilities for software that models and operates utility-scale solar and battery plants. The work combines engineering knowledge of plant performance with machine learning, covering the data foundation, model development lifecycle, and delivery of models that can run at plant sites. You will own models from early prototypes through deployment and ongoing monitoring.

Responsibilities

• Develop predictive models that combine physical understanding of plant behavior with machine learning.
• Create and maintain labeled datasets from operations, maintenance, and field information.
• Build repeatable workflows for model training, evaluation, and deployment.
• Package models for site use and coordinate with infrastructure engineers on deployment.
• Monitor model performance and use observed results to guide improvements.

Requirements

• 6 or more years in software engineering, including at least 3 years building machine learning systems for production.
• Strong Python and SQL skills and practical experience with current machine learning libraries.
• Data engineering experience building dependable pipelines for high-volume sensor or time-series data.
• Familiarity with model training and evaluation workflows, registries, and production monitoring.
• Experience with data lakes, streaming systems, and workflow orchestration.
• Infrastructure-as-code experience, such as Terraform, plus a track record of owning work from prototype to production.

Nice to have

• Knowledge of utility-scale solar or storage operations and performance tools such as PVsyst or SAM.
• Experience blending simulation or physical models with machine learning, or applying linear and mixed-integer optimization.
• Familiarity with inverter behavior, edge deployments, or full-stack software development.

Benefits and work setup

• Remote role based in California, with a stated base salary range of $237,000–$257,500 USD, plus equity and benefits.
• Health coverage includes full employee and partial dependent premiums for a Gold-level PPO plan; dental and vision premiums are partially covered.
• Retirement plan includes a 6% employer match.