Senior Machine Learning Engineer, Toronto

Studiotilt
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Machine Learning Performance Engineer

Senior/Staff Machine Learning Engineer

Senior Backend Engineer – Train in Machine Learning – Full Remote

Senior Machine Learning Engineer, Toronto

Join to apply for theSenior Machine Learning Engineer, Torontorole atTILT.

Tilt

Our mission is to make fashion accessible to all and inspire everyone to dress a little better.We believe e-commerce is in a rut, with brands lost in a decades-long void, lacking innovation, and mindlessly redesigning websites without fixing the real issue making shopping fun and affordable.

Today, we are the UK's biggest live shopping platform focused on making shopping a joyful, social experience that brings people together and helps everyone level up their style.We've raised an $18m Series A, and we're rapidly growing and looking to hire A-players to build the future of shopping.

Your Mission

We are hiring aSenior Machine Learning Engineerfor AI/ML initiatives at Tilt. This is a hands-on role where you'll lead by example, directly contributing to building and scaling AI at Tilt.This is not a management or research position.

You must be prepared to jump into a start-up environment; if you prefer to avoid risks, this isn't the right place for you, so please refrain from applying. We seek passionate, driven individuals eager to learn quickly, work hard, and help us shape the future.

What You'll Do

  • Design, develop and deploy the first-of-their-kind AI-driven features for e-commerce from scratch.
  • Work closely with product, engineering, and design teams to identify and execute high-impact features.
  • Build robust, scalable infrastructure for AI at Tilt.
  • Provide valuable technical guidance for product engineers on building world-class AI systems.
  • Dig deep into existing products, develop plans for improvement and collaborate with the team to execute.

Requirements

You must be an ambitious, curious, relentless and no ego problem-solver excited to build the future of shopping. Additionally:

  • Candidates MUST be ready to join a startup and move fast through interview rounds.
  • Experience taking ML systems from 0 to 1 to large-scale, serving millions of users (LLMs, rec sys, computer vision or NLP).
  • 3+ years of hands-on experience in ML/AI engineering, with proven expertise in building and deploying solutions at scale.
  • Bachelor's degree in a STEM major (mathematics, computer science, engineering).
  • Expertise in Python, PyTorch/TensorFlow and ML frameworks.
  • Comfortable working with our stack (or similar): AWS, OpenSearch, PostgreSQL, Snowflake.
  • Ability to work autonomously to deliver results at a rapid pace.

Bonus

  • Experience with high-traffic, real-time platforms.
  • 1+ years of experience in high-growth, fast-paced environments.

Perks & Benefits

  • Stock Options.
  • MacBook Pro + Tech Budget.
  • Flexible and hybrid working as standard.
  • Canary Wharf office includes gym access.
  • Opportunity for periods of fully remote work, from any location.

Want to join?

Apply with your CV and provide authentic answers to the questions in the application form.

Compensation Range: CA$110K - CA$160K

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology

Industries

Software Development

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.