Senior/Staff Applied Machine Learning Scientist

Full Timestaff

Canada; United StatesPosted 7 weeks ago

Role Overview

Stackadapt is hiring a Senior/Staff Applied Machine Learning Scientist. This is a full-time role in Canada;. Full responsibilities, required qualifications, and the apply link are listed in the description below.

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ROIORPrototypingBenefitsOnboardingPrivacyStackAdaptAI

Job description

StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels.

We are searching for a talented Senior/Staff Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we're dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability.

Want to learn more about our Data Science Team: https://alldus.com/ie/blog/podcasts/aiinaction-ned-dimitrov-stackadapt/

Learn more about our team culture here: https://www.stackadapt.com/careers/data-science

Watch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuU

StackAdapt is a remote-first company, and we are open to candidates located anywhere in the US or Canada for this position.

What you'll be doing:

Lead the creation and optimization of advanced machine learning algorithms—from developing new methods to refining existing techniques—to enhance advertising effectiveness and ROI using deep ML expertise.
Own the end-to-end development of production-grade ML models: write efficient, scalable code and collaborate with Machine Learning Engineers to deploy and integrate algorithms into live systems.
Drive the prototyping and rigorous testing of innovative algorithms and data pipelines using historical data to validate performance and scalability; lead iterative improvements based on data-driven insights.

What you'll bring to the table:

3+ years of industry experience
Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.
Have the ability to take an ambiguously defined task, and break it down into actionable steps
Have a comprehensive understanding of statistics, optimization and machine learning
Are proficient in coding, data structures, and algorithms
Enjoy working in a friendly, collaborative environment with others

StackAdapter's Enjoy:

Highly competitive salary
Retirement/ 401K/ Pension Savings globally
Competitive Paid time off packages including birthday's off!
Access to a comprehensive mental health care program
Health benefits from day one of employment
Work from home reimbursements
Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto
Robust training and onboarding program
Coverage and support of personal development initiatives (conferences, courses, books etc)
Access to StackAdapt programmatic courses and certifications to support continuous learning
An awesome parental leave program
A friendly, welcoming, and supportive culture
Our social and team events!

Please note: Benefits and perks may vary depending on your country of employment and the nature of your engagement. In locations where StackAdapt does not have a legal entity, employment and benefits are administered in accordance with local regulations and partner policies.

StackAdapt is a diverse and inclusive team of collaborative, hardworking individuals trying to make a dent in the universe. No matter who you are, where you are from, who you love, follow in faith, disability (or superpower) status, ethnicity, or the gender you identify with (if you’re comfortable, let us know your pronouns), you are welcome at StackAdapt. If you have any requests or requirements to support you throughout any part of the interview process, please let our Talent team know.

We use artificial intelligence (AI) to streamline the resume reviews of candidates and assess their fit based on the criteria outlined in the job posting. We do not use AI to make any final hiring or interview decisions.

About StackAdapt

We've been recognized for our diverse and supportive workplace, high performing campaigns, award-winning customer service, and innovation. We've been awarded:

G2 Top Software for 2026
2026 Best Workplaces™ for Young Talent and in Canada by Great Place to Work®
#1 DSP on G2 and leader in a number of categories including Cross-Channel Advertising

To learn more about our privacy practices, please see our Privacy Policy.

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About Stackadapt

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Frequently Asked Questions

How do I apply for the Senior/Staff Applied Machine Learning Scientist position at Stackadapt?

Use the Apply button above to submit your application directly to Stackadapt. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.

Where is the Senior/Staff Applied Machine Learning Scientist position at Stackadapt located?

This position is based in Canada;. Stackadapt has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.

What does a Senior/Staff Applied Machine Learning Scientist at Stackadapt earn?

Stackadapt has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.

When was the Senior/Staff Applied Machine Learning Scientist role at Stackadapt posted?

This role was posted on May 19, 2026 (55 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.