Machine Learning Engineer

Leap Tools Inc.; Canada; Remote; CAD 80,000 - 110,000; Full time

Job summary

A leading tech innovator in home décor solutions is seeking a Machine Learning Engineer to spearhead innovative projects that empower users to visualize products in their spaces. You will drive user-centric solutions, work closely with design teams, and utilize advanced algorithms to transform the interior design process. Join a remote-first culture that values creativity, persistence, and collaboration in a fast-paced environment.

Benefits

Generous time off

Work-from-home stipend

Parental leave program

Flexible remote work

Birthday off

Qualifications

• Expertise in driving user-centric machine learning solutions.
• Persistent in solving complex problems independently.
• Strong foundation in computer science and Python coding.
• Hands-on experience in data collection, cleaning, and evaluation.

Responsibilities

• Spearhead machine learning initiatives for home décor visualization.
• Integrate various home essentials for a holistic redecorating experience.
• Implement real-time product rendering based on user preferences.
• Collaborate with design experts to enhance realism in models.

Skills

Machine Learning

Python

Data handling

Problem-solving

Tools

PyTorch

TensorFlow

Django

Kubernetes

Job description

Overview

You're driven by the potential of machine learning and AI in transforming the world. You thrive on crafting intricate algorithms that power seamless, user-centric experiences. Every pixel and every frame matter to you, and you're eager to pioneer solutions that will redefine how people redesign their spaces. Feel like you're on the edge of a breakthrough, but need the right platform? Join us. With our elite tech squad, you'll take our revolutionary digital décor tools beyond the horizon!

At Leap Tools, we are building the world's most advanced solutions for the interior décor industry. With customers in 80+ countries, our clientele includes Fortune 500 companies such as Home Depot, local retailers such as Alexanian's, and everything in between. We have been recognized as one of the fastest-growing tech companies by Deloitte for multiple years in a row, and we are looking for ambitious challenge-seekers to fuel our momentum and help us create an iconic global tech company.

About Our Product

Our technology lets you see products in your own room before you buy. Imagine you want to redesign your home and have been searching for new tiles for your kitchen or a new rug for your living room. You definitely want to make sure it will look good in your space. We enable that through cutting-edge computer vision technology, presented in an extraordinarily simple and accessible way.

Try our rug demo now! Simply upload a picture of your room using your mobile phone and slide the rug under your coffee table.

About you

You have a passion for solving complex problems and working on products used by millions of people. You enjoy setting the bar high and clearing it. You can lead by example, but you know when to step aside and let the team run with the ball. Your technical knowledge is matched only by your passion to design, create, and succeed with others.

You want to build on your experience. You are interested in making a big impact, but perhaps you are currently limited in your growth potential. Join us and you will work directly with our talented engineering team to push our product to new heights.

About our Stack

• Mostly PyTorch, some Tensorflow, as well as our own in-house systems
• Python and Django
• gRPC
• Kubernetes on AWS

What You'll Do

• Innovative Vision: Spearhead machine learning initiatives to instantly generate and visualize a vast array of home décor items, transforming browsers into personalized interior design studios.
• Holistic Redecoration: Use state-of-the-art algorithms to offer users an all-encompassing redecoration experience, seamlessly integrating wallpaper, flooring, countertops, and a plethora of other home essentials.
• Adaptive Product Rendering: Implement machine learning techniques to adapt and present décor products in real-time based on user preferences, room dimensions, and existing furnishings.
• User-Centric Design: Work closely with interior design experts, UX/UI designers, and development teams to constantly refine models and enhance realism.

Requirements

• Your expertise in Machine Learning isn’t just about models and algorithms; it’s about driving tangible, user-centric solutions.
• You are willing and able to tackle unsolved problems without supervision or much guidance after you collaborate with your team members on initial designs.
• You are persistent, despite days, weeks, or even months of disappointing results, maintaining the same level of determination as on day one.
• You have a strong foundation in computer science and are very comfortable coding in Python.
• You have read papers on machine learning topics and implemented your own versions of the papers.
• You're hands-on with data: from collection and cleaning to putting together evaluation sets.
• Challenges? Bring them on. You thrive when you're pushing the boundaries of what Machine Learning can achieve.

About our culture

• We're a remote-first company that encourages our employees to work from where they're most productive.
• We work in tight-knit teams to cultivate an ownership mentality.
• We cherish curiosity and an obsession for details because we know these details are invaluable over the long run.
• We're hyper-focused on our achievements and our ability to execute our promises. We act with urgency.
• We value work-life balance by offering generous time off
• Work anywhere in the world for up to 3 months!
• We value families, by offering a parental leave program
• We offer a work-from-home stipend
• Your birthday (and our company's birthday) is a day off!

About our hiring process

Now: You upload your resume and complete a brief questionnaire.

Steps 1 and 2: Two rounds of technical assessment.

Step 3: Culture fit assessment.

Step 4: Final interview with leadership.

Step 5: You receive an offer.

Take the Leap. Apply now.

Our demo, in case you missed it: