Gaiamesh is a rapidly growing AIoT proptech startup focusing on commercial building energy optimization. We have teams based in Shanghai, Bangkok, Hong Kong, and the USA, and work with industry leaders including JLL, Starbucks, and NYU. About the Role: As Technical Lead for Controls & Optimization reporting to the CEO, you will own the development of advanced control algorithms that deliver measurable energy savings for our customers on top of our current AIoT control system. You will translate our Chief Solutions Officer's domain expertise into production-ready optimization systems using Model Predictive Control (MPC), reinforcement learning, and other cutting‑edge techniques. This is a hands‑on technical role where you will architect, code, and deploy the controls intelligence that differentiates Gaiamesh. This is initially an individual contributor role that can later involve management of direct reports depending on your capability. Location: Hong Kong Technical Challenge: We seek to solve the global problem of overly complex building controls to unlock grid‑integrated building intelligence, overnight. We are focusing on higher‑ed, hotel, and AI datacenter markets. To achieve this, we need you to help us solve the following technical challenges. 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 time‑of‑use 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 Development: Work closely with Chief Solutions Officer to understand customer requirements, control strategies, and M&V methodologies Work closely with our front‑end, back‑end and firmware teams to position the advanced control logic framework within the current system architecture Translate solutions engineering concepts into technical specifications and algorithm designs Define data requirements, sensor placement, and integration points needed for advanced controls Document control strategies in ways that both technical and non‑technical stakeholders can understand Control Algorithm Development: Design and implement control algorithms for HVAC optimization Develop thermal prediction models using physics‑based approaches, machine learning, or hybrid methods Build optimization engines that balance multiple objectives: energy cost, carbon intensity, occupant comfort, and equipment constraints Implement time‑of‑use optimization logic that shifts flexible loads to minimize electricity costs Explore reinforcement learning approaches for control problems where explicit models are difficult to construct Write production‑quality code for optimization algorithms that integrate with our platform Technical Leadership: Establish best practices for controls algorithm development, testing, and validation Share learnings with team members on control theory, optimization methods, and building science Evaluate build vs. buy decisions for optimization components and solver libraries Stay current with advances in MPC, reinforcement learning, and building energy optimization Represent Gaiamesh's technical capabilities to customers and investors Required Skills: Control optimization expertise : Deep understanding of control optimization methods such as Model Predictive Control and Reinforcement Learning with practical implementation experience, including formulating objective functions, constraints, and tuning for real‑world systems Hands‑on coding : Strong Python development skills with experience in numerical computing, optimization libraries, and machine learning frameworks Thermal systems knowledge : Understanding of HVAC systems, chiller plants, and building thermodynamics sufficient to construct physically meaningful models Optimization fundamentals : Solid foundation in mathematical optimization—linear programming, quadratic programming, nonlinear optimization, and when to apply each Systems thinking : Ability to understand complex systems holistically and identify the highest‑leverage control interventions Technical communication : Can explain complex algorithms to solutions engineers and translate domain requirements into technical specifications Fluent English and Mandarin for collaboration with international team and customers Qualifications: 5+ years of progressive experience in product engineering or applied research roles Technical degree in Computer Science, Engineering, or related field (or equivalent practical experience) Experience building B2B software products, automation tools, or AI‑powered applications Experience in technical sales, building/energy industries, or domain‑specific AI applications is a plus Demonstrated ability to work hands‑on with technology - comfortable prototyping, coding, or guiding technical development Ideal Candidate: Builder and maker who loves shipping products that solve real problems and is comfortable with hands‑on technical work Entrepreneurial product leader who thrives in ambiguous environments and can define product vision from scratch Curious technologist who stays current with AI/ML innovations and experiments with new tools and approaches User‑obsessed designer who validates assumptions through research and continuously improves based on feedback Data‑driven decision maker who instruments products, analyzes metrics, and iterates based on evidence Collaborative partner who works effectively with business, technical, and operational stakeholders Comfortable bridging business and technology, translating user needs into technical requirements and vice versa Why Join Gaiamesh: High Impact Role – Build groundbreaking AI products at the intersection of building science, automation, and revenue technology. Shape product strategy for a fast‑growing company with global expansion potential. Define the technical approach for advanced controls from the ground up and help to capture the red‑hot AIDC market Collaborative Culture – Work directly with CEO and Chief Solutions Officer to productize world‑class building science expertise, and alongside a passionate, talented team that values creativity and innovation. Fast‑Paced Learning – Grow your skills rapidly in a dynamic environment with cutting‑edge tech. Generous Share Options – Own a piece of the company and share in its growth as we scale. Flexible Work Location – Work remotely, hybrid, or from our office—whatever suits your lifestyle best. Annual Leave – 15‑day annual leave and reasonable working hours help maintain a healthy work‑life balance. Hiring Process: We strive to respect your time and avoid useless whiteboard reversing of binary trees, so we keep the interview process simple and transparent: Single non‑technical interview with company leadership to ensure fit, A relevant homework assignment requiring less than 4 hours, Final interview to discuss the assignment and meet members of the team, Hiring decision and offer is made after that. Gaiamesh is committed to building a diverse and inclusive workplace. We encourage applications from candidates of all backgrounds. #J-18808-Ljbffr
