Senior/Staff Machine Learning Engineer

StackAdapt Inc.; Toronto; Remote; CAD 170,000 - 234,000; Full time

Benefits offered by this job

Competitive salary

Global retirement plan

Birthday off

Mental health program

Health benefits from day one

Work from home stipend

WeWork membership (global)

Training and onboarding

Personal development support

Programmatic courses & certifications

Parental leave

Friendly culture

Team events

Job summary

StackAdapt is seeking Senior and Staff Machine Learning Engineers to join our Data Science team. You will work directly with Data Scientists, ML engineers, and Engineering teams as well as our CTO on building pipelines and ad optimization models for a high-traffic platform.

StackAdapt is a Remote First company, open to candidates located anywhere in Canada. You will design modular and scalable real-time data pipelines, implement low-latency ML algorithms, and contribute to microservice

Qualifications

• Ability to break down ambiguously defined tasks into actionable steps.
• Proven track record delivering complex projects independently and with teams.
• Strong understanding of algorithms, concurrency, and data structures.
• Experience implementing probabilistic or ML algorithms.
• Experience designing scalable distributed systems.
• High GPA from a respected CS program or equivalent experience.
• Collaborative, friendly team player.

Responsibilities

• Design modular and scalable real time data pipelines to handle huge datasets
• Suggest, implement, and coordinate architectural improvements for big data ML pipelines
• Understand and implement custom ML algorithms in a low latency environment
• Work on microservice architectures that run training, inference, and monitoring on thousands of ML models concurrently

Skills

Real-time pipelines

Big data ML pipelines

Microservices architectures

Low-latency ML

Distributed systems design

Probabilistic ML algorithms

Concurrency & data structures

Education

Computer Science degree

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're looking to add

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're looking to add Senior and Staff Machine Learning Engineers to our Data Science team! This team works on solving complex problems for StackAdapt's digital advertising platform. You'll be working directly with our Data Scientists, Machine Learning engineers, Engineering teams, and our CTO/Co-Founder on building pipelines and ad optimization models. With databases that process millions of requests per second, there's no shortage of data and problems to tackle.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-scienceWatch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuUStackAdapt is a Remote First company, and we are open to candidates located anywhere in Canada for this position.

• Design modular and scalable real time data pipelines to handle huge datasets
• Suggest, implement, and coordinate architectural improvements for big data ML pipelines
• Understand and implement custom ML algorithms in a low latency environment
• Work on microservice architectures that run training, inference, and monitoring on thousands of ML models concurrently

• Have the ability to take an ambiguously defined task, and break it down into actionable steps
• Ability to follow through complex projects to completion, both by independent implementation and by coordinating others
• Have deep understanding of algorithm and software design, concurrency, and data structures
• Experience in implementing probabilistic or machine learning algorithms
• Experience in designing scalable distributed systems
• A high GPA from a well-respected Computer Science program or equivalent experience in a competitive, innovative, tech company
• Enjoy working in a friendly, collaborative environment with others

The compensation range listed for this role reflects the expected base salary for candidates located in the posting country based on a global rate. It is informed by market data and the approved budget for this position. StackAdapt maintains different compensation ranges for roles across other countries and regions, and final offers will be aligned to the candidate’s current location. We do not ask candidates about current or prior salary history, and we will not use such information, if volunteered, in setting an offer.This range represents base salary only. Depending on the role, candidates may also be eligible for additional compensation such as annual bonuses, commissions, equity awards, and a comprehensive benefits package.Factors Influencing Final Compensation:The final compensation offer will be determined by a variety of factors, which may include, but are not limited to: the candidate's specific experience, technical skills, knowledge, abilities, and relevant education, licensure, and certifications.Other business factors, such as organizational needs and budget alignment, may also be considered in the final offer.

Base Salary Band: $170,400 CAD - $234,300 CAD

• 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, superpower status, ethnicity, or the gender you identify with (if you’re comfortable, let us know your pronouns), you are welcome at StackAdapt.

StackAdapt is committed to providing an inclusive and accessible recruitment process. Accommodations are available upon request for candidates taking part in all aspects of the selection process. If you require an accommodation, please let us 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 StackAdaptWe'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