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StackAdapt

Machine Learning Engineer (Remote)

Reposted 17 Days Ago
In-Office or Remote
Hiring Remotely in California, USA
140K-193K Annually
Mid level
In-Office or Remote
Hiring Remotely in California, USA
140K-193K Annually
Mid level
Design and implement scalable data pipelines and ML algorithms to optimize StackAdapt's digital advertising platform. Collaborate with teams to solve complex problems.
The summary above was generated by AI

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 a Machine Learning Engineer 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.
 
StackAdapt is a remote-first company with teams around the world. Our teams work in a fully distributed environment, and we are open to candidates based in Canada and the United States.
 
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
What you'll be doing:
  • Design modular and scalable real time data pipelines to handle huge datasets
  • 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
What you'll bring to the table:
  • Have the ability to take an ambiguously defined task, and break it down into actionable steps
  • Have deep understanding of algorithm and software design, concurrency, and data structures
  • Experience in implementing probabilistic or machine learning algorithms
  • Interest in designing scalable distributed systems
  • A high GPA from a well-respected Computer Science program
  • 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.
Canada Base Salary Band
$140,000$192,500 CAD
USA Base Salary Band
$128,000$176,000 USD
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, 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.
 
#LI-REMOTE

StackAdapt Los Angeles, California, USA Office

Los Angeles, United States

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