Posted today
Location: Chile (Or availability to relocate to Santiago de Chile)
Employment Type: Full-time employee contract.
Working hours: 9:00 AM–6:00 PM Chile time, with flexibility. Friday are remote!
Compensation: $4,500–$6,000 USD/month
Tech Stack: Python, machine learning, predictive modeling, forecasting, reinforcement learning, AI agents, agent orchestration, and cloud infrastructure.
At Near, we connect top talent in Latin America with exciting opportunities at high-growth companies. Our mission is to create better lives by fostering a work culture that transcends borders.
Our client is an early-stage energy technology company building an AI-powered platform for battery and energy-retail operations.
Their technology uses predictive models and an AI Dispatch Optimizer to determine when batteries should charge and discharge, helping maximize savings at each site. An initial version of the platform is already deployed across pilot battery sites, with machine learning models and predictive algorithms running in real-world environments.
The company is now expanding the platform into an AI-driven operating system designed to automate energy-retailer workflows end to end.
We’re looking for an AI / Machine Learning Engineer to strengthen the company’s predictive and optimization capabilities while contributing to the next generation of its AI platform.
Your primary focus will be improving models for energy demand and pricing forecasting, enhancing the AI Dispatch Optimizer, and exploring techniques such as reinforcement learning to increase the value generated by each battery site.
You will also contribute to the company’s AI agent orchestration layer and broader automation initiatives.
This is a foundational role in a growing startup, working closely with the CEO, who currently leads the technical and product functions. You’ll have significant ownership and the opportunity to influence how the platform evolves.
Improve machine learning models used to forecast energy demand and energy prices.
Enhance the AI Dispatch Optimizer that determines optimal battery charging and discharging.
Explore and implement reinforcement learning and other AI approaches to improve site-level savings and performance.
Test and compare forecasting architectures, predictive models, and feature-engineering approaches.
Work with historical and real-world data to improve model accuracy and reliability.
Develop and refine predictive engines using multiple data inputs and signals.
Contribute to an AI agent orchestration layer that coordinates agents across energy-retailer operations.
Support AI-driven automation across areas such as billing, CRM, customer success, acquisition, sales, support, installation, and operations.
Help shape technical decisions as the platform scales across Latin America.
3+ years of hands-on experience in machine learning, data science, predictive modeling, or related work
Proven experience building, deploying, or improving machine learning models in real-world environments.
Strong understanding of forecasting, predictive modeling, machine learning algorithms, and model evaluation.
Strong Python skills for data science and machine learning.
Experience with feature engineering and combining multiple data sources or signals to improve model performance.
Strong problem-solving skills and a hands-on approach to testing, iterating, and delivering solutions.
Ability to work independently with limited supervision while collaborating closely with a technical founder.
Comfort working in an early-stage startup
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
Ability to communicate effectively in English
Experience with reinforcement learning.
Experience building AI agents, LLM applications, or agent orchestration systems.
Experience using AI to automate operational or business workflows.
Familiarity with TensorFlow, Hugging Face, or similar machine learning frameworks.
Experience setting up cloud compute environments for model training and deployment.
Background in energy, electricity markets, batteries, energy forecasting, or optimization.
Previous early-stage startup experience.
Familiarity with modeling approaches such as Transformers, Temporal Fusion Transformers, random forests, regression-based forecasting, or comparable architectures.
$4,500–$6,000 USD/month,
Competitive equity package
Full-time employee contract in Chile.
One regular remote workday per week, typically Friday.