Jobs / United States / Stackadapt

Stackadapt

Machine Learning Engineer (Remote)

Location unlisted Posted today £82,125 — £112,922

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Sponsorship verdict

No sponsorship evidence yet

No government record and no wording either way. Not a refusal: ask the recruiter.

  • No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Stackadapt paid sponsored hires in similar roles5 certified filings for “Applied Machine Learning Scientist” (Data Scientists) in IL: $150k–$220k, median $169k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Stackadapt paid sponsored hires in similar roles
5 certified filings for “Applied Machine Learning Scientist” (Data Scientists) in IL: $150k–$220k, median $169k. Most were filed at wage level IV (60%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

Before you apply

Sponsorship unknown

No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.

These come from the posting’s own wording. Read the original listing to confirm. See better-fit alternatives →

About the 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/ 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 c andidates 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 fr

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