[All remote jobs](https://jobicy.com/jobs.md)[![StackAdapt logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2022/01/bf5f2bb689c6f35f6cab5459f3eff869.jpg)](https://jobicy.com/company/stackadapt.md)[StackAdapt](https://jobicy.com/company/stackadapt.md) # Machine Learning Engineer Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/stackadapt.md)ShareRemote from[UK](https://jobicy.com/job-region/uk.md), [Germany](https://jobicy.com/job-region/germany.md), [Ireland](https://jobicy.com/job-region/ireland.md)SalaryGBP 82,125–112,922 / yrDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceOpen levelPublished18 Oct 2026Apply before17 Nov 2026Listing views42Application actions2Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. StackAdapt is hiring a Machine Learning Engineer for its Data Science team to build high-throughput data pipelines and low-latency advertising optimization models. The role involves implementing custom machine learning and probabilistic algorithms within distributed microservice architectures for training, inference, and monitoring. Engineers will work closely with data scientists, engineering teams, and the CTO/Co-Founder on systems operating at substantial scale. Candidates must be based in the UK, Ireland, or Germany and should be comfortable turning ambiguous problems into practical technical plans. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a highly technical machine-learning systems role requiring strong algorithmic foundations, concurrency knowledge, and experience building scalable distributed services. The low-latency environment and thousands of concurrently managed models add substantial production-engineering complexity. ## Salary analysis Estimated compensation compared with the broader UK market for similar roles. Estimated job median (per year)Market rate£97,523.50UK market range (per year)£80k–£120k0£132k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a base salary band of £82,125–£112,922 GBP. The yearly cadence is inferred from the level and magnitude of the stated full-time professional base-pay range, as the posting does not explicitly state a period. A reasonable estimated annual market range for a machine learning engineer in the eligible markets is £80,000–£120,000 GBP. ## Core skills Skills and capabilities most closely associated with this opportunity. [Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Probabilistic Modeling](https://jobicy.com/jobs?search_keywords=Probabilistic%20Modeling.md)[Real-Time Data Pipelines](https://jobicy.com/jobs?search_keywords=Real-Time%20Data%20Pipelines.md)[Distributed Systems](https://jobicy.com/jobs?search_keywords=Distributed%20Systems.md)[Microservices](https://jobicy.com/jobs?search_keywords=Microservices.md)[Model Training](https://jobicy.com/jobs?search_keywords=Model%20Training.md)[Model Inference](https://jobicy.com/jobs?search_keywords=Model%20Inference.md)[Model Monitoring](https://jobicy.com/jobs?search_keywords=Model%20Monitoring.md)[Low-Latency Systems](https://jobicy.com/jobs?search_keywords=Low-Latency%20Systems.md)[Concurrency](https://jobicy.com/jobs?search_keywords=Concurrency.md)[Data Structures](https://jobicy.com/jobs?search_keywords=Data%20Structures.md)[Algorithm Design](https://jobicy.com/jobs?search_keywords=Algorithm%20Design.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[Scalable Architecture](https://jobicy.com/jobs?search_keywords=Scalable%20Architecture.md) Sample interview questionsHow would you design a real-time pipeline for generating features and serving predictions under strict latency constraints?I would separate offline and online feature workflows while maintaining feature-definition consistency. For online serving, I would use a low-latency feature store or cache, versioned model artifacts, asynchronous event ingestion, and clear latency/error budgets. I would instrument feature freshness, prediction latency, and fallback behavior from the start. Describe how you would operate thousands of machine learning models concurrently in production. I would standardize model packaging, metadata, deployment, and monitoring through a shared platform. Models would be versioned and registered with automated validation, canary releases, resource limits, and rollback paths. Monitoring would cover service health, latency, prediction distributions, data quality, drift, and model-specific business metrics. What trade-offs do you consider when implementing a custom probabilistic algorithm for a low-latency system? I first identify the minimum accuracy and uncertainty-calibration requirements, then assess the computational cost of exact versus approximate inference. I would favor vectorization, precomputation, bounded memory use, and parallel-safe data structures where appropriate. I would validate that approximations preserve the metrics that matter before deploying them. Tell us about a time you received an ambiguous technical problem. How did you turn it into an execution plan? I clarify the target outcome, constraints, stakeholders, and success metrics, then write down assumptions and risks. I break the work into small experiments or milestones that reduce the highest uncertainties first. I communicate findings early and revise the plan as evidence becomes available. How would you investigate a sudden degradation in model performance on an advertising optimization platform? I would first confirm whether the issue is real by checking metric definitions, data completeness, and monitoring health. Next, I would compare recent traffic, features, labels, model versions, and serving behavior against a stable baseline to isolate likely causes such as drift, pipeline failures, or deployment changes. I would mitigate through rollback or safe fallback behavior while documenting the root cause and adding preventive monitoring. Opportunity details ## About this role. 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/](https://alldus.com/ie/blog/podcasts/aiinaction-ned-dimitrov-stackadapt/) Learn more about our team culture here: [https://www.stackadapt.com/careers/data-science](https://www.stackadapt.com/careers/data-science) Watch our talk at Amazon Tech Talks: [https://www.youtube.com/watch?v=lRqu-a4gPuU](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. 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. 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 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). #LI-REMOTE Show more [Apply now >](https://jobicy.com/jobs/155653-machine-learning-engineer-4.md) * ![Upload CV](data:image/svg+xml;base64,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) ### Upload your resume now To unlock remote work opportunities and be discovered by global employers. 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