Lead the development and optimization of machine learning algorithms, owning the end-to-end model development and collaborating with Data Engineers for integration into live systems.
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 UK 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 Data 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
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
£102,656—£141,152 GBP
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
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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