Software Engineer, Applied AI & Data Systems

About RAKE ML

RAKE ML is building frontier AI systems to understand how the physical world changes over time. The physical systems we rely on every day: homes, roads, bridges, dams, power grids, and other critical infrastructure, are rapidly aging and exposed to climate volatility and accelerated demand. Our mission is simple - help make the infrastructure we depend on safer, more sustainable, and more resilient.

We build AI systems that learn directly from the physical world, then use simulation and machine learning to scale that understanding across assets, climates, and time.
Our goal is to give the people responsible for the built world — from owners and insurers to service providers, utilities, and public agencies — the intelligence they need to make better decisions earlier, faster, and with more confidence.

About the Role

We are hiring a software engineer to help build core systems at RAKE ML. You will be the second engineer on a scrappy, growing team, and a huge part of our story as a company going forward.

This is a high-ownership role for someone who wants to build at the intersection of software engineering, applied machine learning, product development, and physical-world AI.
You will have the opportunity to own critical projects end-to-end: understanding the client problem, designing the system, building the product, evaluating whether it works, and iterating directly from feedback. Your work will directly serve core clients and help shape both the product and technical foundation of the company.

Because we are a small team, you will wear multiple hats. Depending on the project, you may work across backend systems, frontend interfaces, applied ML research, model workflows, product decisions, client conversations, and company strategy.

This role is ideal for someone early in their career who wants a steep learning curve, real ownership, close mentorship from founders, and the chance to help build an ambitious AI company from the ground up.

What You’ll Work On

You may work on projects such as:

• Building AI-native systems that turn messy physical-world information into structured intelligence
• Owning product and engineering workstreams end-to-end, from problem definition through deployment and iteration
• Developing applications where LLMs, machine learning models, and other AI systems are central to the product
• Experimenting with applied ML approaches for physical asset understanding, visual reasoning, temporal change detection, and real-world modeling
• Building full-stack product experiences that bring model capabilities into client workflows
• Working directly with founders on product strategy, technical direction, client needs, and company priorities
• Speaking with clients to understand their workflows, constraints, incentives, and decision-making processes
• Turning ambiguous business and technical problems into clear systems, products, and experiments

Our Current Stack

Our stack is evolving, but today we primarily use:

• Python for backend systems, data processing, ML workflows, and application logic
• React for frontend interfaces
• Multiple cloud environments
• LLMs, machine learning models, and data pipelines as core product components

We do not expect you to have worked with every part of our stack before. We do expect strong Python ability, strong computer science fundamentals, and the ability to learn quickly.

What We’re Looking For
We are looking for someone early in their engineering career who is technically strong, curious, detail-oriented, and excited to improve quickly.

You might be a strong fit if you:

• Have very strong computer science fundamentals
• Are strong in Python and comfortable using it as a primary engineering language
• Can reason clearly about systems, data structures, debugging, architecture, performance, and tradeoffs
• Are deeply curious and enjoy learning new technical domains
• Are interested in using theory, research, and first-principles thinking to drive real applied advances
• Enjoy experimenting, iterating, and learning quickly — while still executing carefully
• Care about details, correctness, and whether systems work under messy real-world conditions
• Can quickly and deeply understand a client’s business needs, incentives, and operating constraints
• Can connect technical decisions to product goals and company strategy
• Are comfortable with ambiguity and self-directed work
• Communicate clearly, ask good questions, and actively seek feedback
• Are excited by physical-world problems: buildings, infrastructure, weather, asset degradation, risk, resilience, and sustainability

Nice to Have

None of these are strict requirements, but they are helpful:

• Deep interest in the physical world: buildings, infrastructure, climate, materials, cities, energy, or asset management
• Experience in or exposure to real estate, construction, development, property and casualty insurance, infrastructure, utilities, or government agencies related to housing, public works, or physical infrastructure
• Coursework or research experience in civil engineering, materials science, mechanical engineering, meteorology, environmental engineering, urban systems, or a related field
• Experience doing machine learning research or applied ML experimentation
• Experience with computer vision, geospatial analysis, simulation, temporal modeling, or world models
• Experience with graphics, 3D, or simulation tools such as Blender, Unreal Engine, Omniverse, or related systems

Why Join RAKE ML

RAKE ML is a small team taking on a big, exciting problem: helping AI understand how the physical world changes over time.

You will get to work on frontier AI while staying close to real users, real assets, and real-world impact. The work is technical, varied, and grounded: one week you may be improving a model workflow, the next you may be shaping a client-facing product, digging into a new physical domain, or helping decide what the company should build next.

Because the team is small, your work will matter quickly. You will have room to own important projects, learn across the stack, talk to clients, contribute to product direction, and grow alongside the company.

We are building RAKE for people who are energized by hard problems, high standards, and practical impact. If you want to become a stronger engineer while working on AI for the buildings and infrastructure people depend on every day, we’d love to meet you.

Location and Work Authorization

This is a remote role based in Canada.

Candidates must be legally authorized to work in Canada.

For employees who are legally eligible and interested in working with us in NYC, we may cover immigration counsel and documentation support for U.S. work authorization via TN status where applicable.

How to Apply

Please send your resume, LinkedIn, GitHub, portfolio, or any projects you are proud of.