Technical Lead Controls & Optimization

About The Role

As the Technical Lead Controls & Optimization at Gaiamesh, reporting directly to the CEO, you will own the development of advanced control algorithms that deliver measurable energy savings. You will translate the Chief Solutions Officer's domain expertise into production-ready optimization systems using Model Predictive Control (MPC), reinforcement learning, and other advanced techniques. This hands-on technical role involves architecting, coding, and deploying the controls intelligence that differentiates Gaiamesh. Initially an individual contributor role, it has the potential to evolve into managing direct reports based on your capabilities.

Technical Challenge

The role focuses on solving global building controls complexities to unlock grid-integrated building intelligence in higher-ed, hotel, and AI datacenter markets. Key challenges include:

• Predict thermal loads and optimize HVAC setpoints in real-time.
• Sequence central plant equipment (chillers, pumps, cooling towers) for minimum energy cost.
• Shift flexible loads to off-peak hours based on electricity pricing.
• Defer AI compute workloads in data centers based on cooling capacity and energy prices.
• Deliver guaranteed energy savings with sub-one-year payback.

What You Will Do

Advanced Controls Architecture Definition: Work with the Chief Solutions Officer to understand customer requirements, control strategies, and M&V methodologies. Collaborate with front-end, back-end, and firmware teams to integrate advanced control logic into the platform. Translate solutions engineering concepts into technical specifications and algorithm designs, while defining data requirements and sensor integration points.

Control Algorithm Development: Design and implement control algorithms for HVAC optimization, develop thermal prediction models using physics-based approaches or machine learning, build optimization engines balancing energy cost, carbon intensity, comfort, and equipment constraints, and explore reinforcement learning techniques for complex control problems. All work is implemented with production-quality code.

Technical Leadership: Establish best practices for algorithm development, testing, and validation. Share insights on control theory and optimization methods, evaluate build vs. buy decisions, and represent Gaiamesh's technical expertise to customers and investors.

Required Skills & Qualifications

Strong understanding of control optimization techniques (MPC, Reinforcement Learning) with hands-on Python coding skills. Deep knowledge of thermal systems, HVAC, chiller plants, and building thermodynamics. Proficiency in mathematical optimization (linear, quadratic, nonlinear programming) along with solid technical communication skills in both English and Mandarin. A technical degree in a related field and 5+ years of relevant experience are required.

Why Join Gaiamesh

Join a high impact role where you build groundbreaking AI products at the intersection of building science, automation, and revenue technology. Work directly with top company leadership, enjoy flexible work arrangements, competitive share options, and a supportive, collaborative culture dedicated to continuous learning and innovation.

Hiring Process

The interview process is simple and transparent: a non-technical leadership interview, a short homework assignment, a final interview to discuss your work, followed by a hiring decision.

Key skills/competency

• Control Optimization
• Model Predictive Control
• Reinforcement Learning
• Python
• HVAC Systems
• Thermal Modeling
• Optimization
• Building Science
• AIoT
• Technical Leadership