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StackAdapt

Machine Learning Engineer (Remote)

United Kingdom
Posted 9 days ago
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StackAdapt - Machine Learning Engineer

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 the UK, Ireland, or Germany.

This role will remain open until February 27, 2026. Applications will be reviewed on a rolling basis, and the posting will close once the deadline is reached.

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 a 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

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

Start with a chat, not a search bar

Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.

Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

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
£82,125—£112,922 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.

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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
https://www.stackadapt.com/resources/blog/g2-2026-best-software-awards

2026 Best Workplaces™ for Young Talent
https://www.greatplacetowork.ca/en/bestworkplaces/best-workplaces-for-young-talent/2026 and in Canada
https://www.stackadapt.com/resources/blog/great-place-to-work-best-workplaces-canada-2026 by Great Place to Work®

#1 DSP on G2 and leader in a number of categories including Cross-Channel Advertising
https://www.stackadapt.com/resources/blog/best-cross-channel-advertising-platform

2026 Winner in the (CTV/OTT) Product/Platform category for the 2026 ADWEEK Tech Stack Awards
https://www.stackadapt.com/resources/blog/adweek-tech-stack-awards-2026

To learn more about our privacy practices, please see our Privacy Policy
https://www.stackadapt.com/legal-document-centre/website-and-platform-user-privacy-policy

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Skills

Algorithm Design
Software Design
Concurrency
Data Structures
Machine Learning Algorithms
Scalable Distributed Systems
Real Time Data Pipelines
ML Algorithms Implementation
Low Latency Environment
Microservice Architectures
Training
Inference
Monitoring
Data Science
Engineering

Location

United Kingdom

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