Job Title: AI Optimization Engineer

Location: Singapore

Company Overview

Our client is a fast-growing global energy technology company focused on advancing next-generation revenue optimization and intelligent energy management solutions. Their core capabilities span Battery Energy Storage Systems (BESS) and Virtual Power Plant (VPP) platforms across residential, commercial & industrial (C&I), and utility-scale applications.

Operating across international electricity markets, they leverage advanced algorithms, machine learning, and real-time optimization to enhance energy trading performance, fleet dispatch efficiency, and overall asset profitability. Their mission is to accelerate the transition to smarter, more resilient, and economically efficient energy systems through data-driven innovation.

Role Overview

We are seeking an AI Optimization Engineer to develop and deploy advanced forecasting and optimization algorithms into live production environments.

This role sits at the intersection of:

Machine Learning & Reinforcement Learning
Power Market Optimization
Energy Trading
Forecasting & Dispatch
Distributed Energy Systems

You will play a key role in driving algorithmic decision-making that directly impacts trading performance, dispatch quality, and revenue generation across distributed energy assets.

This is a highly applied, production-focused role with end-to-end ownership-from research and offline validation to deployment, monitoring, and continuous optimization.

Key Responsibilities

Develop forecasting and optimization models for electricity markets, battery dispatch, and VPP operations
Design and enhance strategies for energy trading, ancillary services participation, and distributed energy resource optimization
Build, deploy, and maintain production-grade models (e.g., ML, RL, MPC, optimization algorithms) in live environments
Continuously improve algorithm performance, operational stability, and revenue outcomes
Collaborate cross-functionally with EMS, cloud platform, firmware, and operations teams to support large-scale deployment
Adapt and localize algorithm strategies for international electricity markets (e.g., Australia NEM, European markets)

Preferred Technical Background

Experience in machine learning, reinforcement learning, model predictive control (MPC), operations research, or optimization systems
Familiarity with optimization solvers such as Gurobi or CPLEX
Experience with time-series forecasting methods
Proven experience deploying algorithms into production systems
Exposure to cloud-native or distributed system environments is advantageous

Requirements

5+ years of experience in algorithm engineering, optimization, applied machine learning, or related fields
Strong track record in building and delivering production-grade optimization or ML systems
Experience in forecasting, optimization, dispatch, recommendation, control, or decision-making systems
Strong engineering mindset with end-to-end ownership
Experience in energy storage, VPP, EMS, electricity markets, or energy trading is preferred
Familiarity with deregulated electricity markets (e.g., Australia NEM, Europe, ERCOT, CAISO) is highly advantageous
Candidates from adjacent domains such as quantitative optimization, autonomous systems, logistics optimization, trading systems, or large-scale real-time decision systems are encouraged to apply

If you have the right skillsets for this role, please do not hesitate to apply!