Machine Learning Engineer (Remote)

StackAdapt Inc.; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

StackAdapt is seeking a Machine Learning Engineer to join its Data Science team. You will design modular, real-time data pipelines to handle massive datasets and implement custom ML algorithms in a low-latency environment.

You will work with microservices that run training, inference, and monitoring on thousands of ML models in a scalable distributed system. A strong CS background and high GPA are valued in our remote-friendly, global team.

Qualifications

• 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.
• 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.
• Enjoy working in a friendly, collaborative environment with others.

Responsibilities

• 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

Skills

Real-time pipelines

ML algorithms

Microservice architectures

Distributed systems

Ambiguity to action

Collaborative environment

Education

High GPA CS program

Job description

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 compensatio