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Software Engineer

Thermolio AI1 day ago
Montreal, Quebec, Canada
Mid Level
Full-Time

Top Benefits

Competitive base salary
Performance bonus
Equity package

About the role

Company Description

Thermolio is a cutting-edge real-time HVAC AI platform designed to empower building teams by delivering predictive maintenance alerts, minute-by-minute system optimization, and a unified data layer for BAS/CMMS. Our solution helps commercial and institutional building owners monitor performance, reduce energy consumption, and improve operational efficiency through software-defined automation and analytics. Headquartered in Montreal, Thermolio operates at the intersection of software engineering, data infrastructure, and applied AI for the built environment.

What you'll do

You will lead the development of a new AI-enabled diagnostics and monitoring platform designed for enterprise building portfolios. This role is software-engineering first, with applied ML integrated into production systems.

Responsibilities

Designing, building, and deploying production-grade backend services using Python and FastAPI Developing and maintaining modern web applications using React.js and Next.js (TypeScript) Implementing proof-of-concept and production features that integrate PyTorch / TensorFlow models where required Building and automating robust data pipelines to ingest, clean, validate, and process large-scale system and financial data Setting up and maintaining CI/CD pipelines, infrastructure-as-code, and secure cloud deployments on AWS or Azure Collaborating closely with the founder and a small, high-impact engineering team to translate ideas into working software Delivering end-to-end features, demos, and product milestones on a predictable 4-week development cycle

Who you are? 2+ years of experience building, deploying, and maintaining software or data-intensive systems in production Strong proficiency in Python, with hands-on experience building APIs using FastAPI Solid experience with React.js and Next.js, including frontend-backend integration Practical understanding of large-scale systems, data pipelines, and financial or time-series data Experience owning projects end-to-end: design → implementation → deployment → monitoring Ability to work autonomously, make pragmatic engineering decisions, and deliver under tight timelines

Experience with machine learning is valued, this role prioritizes strong software engineering, system design, and production delivery.

Why join Thermolio?

Competitive base salary, performance bonus, and equity package

High-impact work with institutional clients across global financial markets Full-time role based in our Montreal HQ, with flexible remote days Professional development budget and leadership growth opportunities A fast-moving, innovation-driven team with minimal bureaucracy

How to apply

Please include

A one-page résumé or a link to your GitHub / portfolio A short note (max 200 words) about a machine learning or software project you shipped quickly to technology@themrolio.com

Location: This is an in-person role at our Downtown Montreal office. Remote work options are not available for this position.

We move fast. Qualified applicants will receive an interview invite within 72 hours.

Thermolio AI does not accept unsolicited candidate resumes or profiles from external sources such as recruitment firms, headhunters, or employment placement agencies with whom we do not have a contractual relationship. Any candidate information or resume received, directly or indirectly, from a headhunter, agency or recruiter with whom we do not have a contractual relationship will be disregarded, and, under no circumstance, will we pay any referral, placement, or other fee for the supply of such unsolicited resumes or information.

About Thermolio AI

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Thermolio AI leverages autonomous AI agents, predictive analytics, and wireless sensor networks to optimize thermal asset management and reduce energy consumption without human intervention. Validated through university research, Thermolio enables energy savings of up to 40%, proactively predicts maintenance needs, enhances occupant comfort, and significantly decreases buildings' carbon footprint—all achievable with minimal capital expenditure.

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