---
title: 'Senior Machine Learning Engineer at CloudX'
canonical: 'https://feeny.ai/job/senior-machine-learning-engineer-cloudx-global-fb0dexdb7jhd'
type: 'job'
last_seen: '2026-09-05'
---

# Senior Machine Learning Engineer at CloudX

- **Company:** CloudX
- **Location:** Global
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-04-30
- **Last confirmed live:** 2026-09-05
- **Apply:** https://jobs.gem.com/cloudx/am9icG9zdDrxLIPN0AOjuHIZml-ndkRU

## Job description

Senior Machine Learning Engineer

## About CloudX

At CloudX we’re building a new supply-side advertising platform for mobile publishers. We’re convinced that an AI-native product will significantly advance the state of the art in mobile advertising; we [recently raised a $30M Series A](https://www.cloudx.io/posts/hello-world) in order to bring this dream to life. We have a long history of innovation in this space — our founding team previously built MoPub (sold to Twitter for $350M) and MAX (acquired by AppLovin). Our new platform combines real technical improvements like [verifiably fair auctions](https://www.cloudx.io/posts/the-trust-problem-in-ad-tech-and-how-we-solved-it) with a truly [AI-native product experience](https://www.cloudx.io/posts/monetization-as-code) to give publishers unprecedented control over their ad monetization strategy.

## About The Team

Our Engineering team is distributed and remote — spanning UTC-8 to UTC+6, with core working hours of roughly the US Eastern business day. We have a strong ownership culture and are heavily collaborative, relying primarily on asynchronous, written, communication for coordination. We ship daily and believe that fast CI and good test coverage is the best way to remain productive as we scale. We’re small and high trust; we optimize for rapid iteration and experimentation. Everyone has access to the latest AI tools, but rather than generating vibe-slop we use them pragmatically to build better products. We are lucky to work closely with our talented Product and Business teams to make sure we’re building the right things. It’s a true early-stage startup with lots of important work to go around.

## What you'll do

We are looking for a Senior Machine Learning Engineer to own one of the most important product bets we're making: replacing the narrow set of manual knobs our publishers use to drive revenue — per-line-item floors, bidder targeting, waterfall ordering — with ML-driven systems that optimize life-time customer value automatically. Our long-term vision is for CloudX to be the simplest ad monetization platform; customers express their basic constraints and desired ad setups, and our machine learning algorithms and agents work together to make suggestions and work within those constraints in order to maximize LTV.

You will be our first dedicated ML hire and you will be directly responsible for delivering this vision.

We’re looking for someone with hands-on experience actually training and deploying traditional machine-learning models. Think: Thompson sampling, generalized policy learning, LightGBM. Your key responsibilities will be:

- Machine Learning Engineering: design, train, evaluate, and ship the models that power the revenue-optimization product. You'll own the full lifecycle, from feature definition through production deployment and online evaluation. You'll make the architectural calls — what models, what training framework, what serving approach — and you'll write the code to make them real.
- Product Ownership: the "make me more money" button is a multi-year product surface, starting with floor pricing, extending into waterfall and bidder-order optimization, and eventually joint optimization across the full set of publisher controls. You'll work directly with Product and with publishers to understand what's actually worth optimizing for and sequence the roadmap accordingly.
- Technical Leadership: lead by example to build out the ML discipline at CloudX. Today, several engineers across backend and infra contribute to the ML effort as part of their broader work; you'll be the person setting direction, raising the bar, and — as the function grows — helping us hire and mentor additional ML engineers.

## Who you are

We're looking for someone who has done this before. The skill we are hiring for is specifically the ability to take an ML system from "theoretically promising" to "demonstrably moving real revenue in production", and we'd like to see concrete evidence of that in your past work. We encourage you to apply if you meet these requirements:

- You've shipped ML into a production request path. Not a batch job, not a notebook, not a dashboard. A model serving real traffic under a latency SLO, where getting it wrong costs money. You can talk about a specific system you built, the lift you measured, and how you measured it.
- You've owned the offline-to-online feature parity problem. You've seen training/serving skew, you've written (or reviewed) the featurizer that runs in both places, and you have a view on how to keep them consistent as the system evolves.
- You've run real experiments measuring real revenue impact. You understand the difference between "the model log-likelihood improved" and "the business made more money," and you can describe a time those disagreed and what you did about it.
- You can get comfortable outside Python. You tell us what you need for the models, but the rest of our services are mostly Golang. You don't need to be a Go engineer, but you should be willing to learn enough to read production serving code, flag where it diverges from training, and contribute fixes when it does.
- Hands-on expertise: in case we weren’t clear enough already, this is a hands-on position. You may have managed or led ML teams at points in your career, but you still code regularly and are interested in continuing to do so. You've owned large projects end-to-end and know how to work well with others.
- Strong written communication skills: you are used to writing about, speaking about, and generally communicating complex technical subject matter both to other engineers and to non-engineers.
- Early-stage mentality: you understand that success at a startup involves grit and determination. You have good taste when it comes to trading off speed vs. perfection. You know when to cut corners but aren't afraid to advocate for rigor when you believe it's necessary.
- AI forward: you are actively experimenting with or using AI as part of your software engineering practice. You don't send vibe-coded slop to your teammates to review, but you use AI appropriately to achieve great results.
- High ownership: you care a lot about your work and when you ship a product, you make sure it continues to solve problems for the customer. You care a lot about the customer, the overall business, and are constantly trying to help achieve success — with or without code.

While not strictly required, we're particularly interested in candidates with:

- Adtech experience: you've worked in adtech — SSP, DSP, ad exchange, RTB — and have a good understanding of the broader ecosystem and market. Equivalent experience from other low-latency, revenue-objective ML domains (search ranking, recsys, marketplace pricing for rides/delivery/lodging, or quant execution) is a real substitute and we'll treat it as such.
- Auction and bidding model experience: hands-on experience with contextual bandits, reinforcement learning, Thompson sampling, or other approaches that fit the explore/exploit structure of auction pricing. Familiarity with the RTB literature or systems like Meta's Pearl is a strong positive.
- Stack experience: we're running in AWS, our inference is ONNX-based, we currently train with XGBoost (and are evaluating LightGBM), we use ClickHouse for analytics, Kubernetes for training orchestration, and Datadog for observability. All of this is v0; we'd be happy to speak with you if you have strong opinions about the right tools for the job.

In general, we’re looking for people with grit, passion, and talent. If you’re not sure if this role is an exact fit, we encourage you to apply. Many members of our team have had interesting career paths and we relish the chance to work with extraordinary individuals.

Pay and Benefits

The annual US base salary range for this role, and other engineering roles, is $150,000 – $300,000. This salary range is broad in order to accommodate a wide range of candidates; the interview process will narrow it down based on a number of factors, including your experience, qualifications, and location.

We offer equity compensation and top-tier medical, dental, and vision benefits.

We also have a generous hardware budget for a computer, monitor, and other core equipment necessary to work effectively on a remote team.

We care about the quality of your work more than the specific hours you spend getting it done, and try to minimize the number of synchronous meetings in favor of greater flexibility. There is no in-office requirement.

## About CloudX

## Company Overview
- **One-liner**: CloudX is an AI-native supply-side platform (SSP) for mobile and AI publishers, rebuilding publisher monetization infrastructure for the intelligence era.
- **Entity Type**: Private (Series A)
- **Headquarters**: Suffield, Connecticut, USA (also offices in San Francisco, New York, Las Vegas, Aspen)
- **Founded**: 2025
- **Founders**: Jim Payne (Founder & CEO), Jack Kern (Co-Founder & Chief of Staff)

## Core Business
- **Primary industry**: AdTech / Mobile Advertising / Artificial Intelligence
- **Target customers**: Mobile publishers, AI-native publishers, app developers (B2B)
- **Mission or purpose**: To redefine the future of mobile advertising by providing a secure, transparent, AI-native auction infrastructure that puts publishers first, leveraging Trusted Execution Environments (TEE) and real-time intelligence.

## Products & Services
- **CloudX SSP (Supply-Side Platform)**: Core platform that provides a liquid marketplace, AI workflows, and real-time bid optimization for mobile and AI publishers. Includes a secure, AI-native auction infrastructure powered by TEE.
- **CloudX Agent**: An AI-powered assistant that lets publishers interact with their inventory via natural language—review metrics, run A/B tests, update pricing strategies, or get integration help. Available in beta from every page in CloudX.
- **Total Revenue Dashboard**: A unified reporting view that consolidates data from multiple platforms, addressing reporting complexity for multi-platform publishers.
- **DT SDK Bidder**: A new demand source that matches performance and brand demand across all formats, now live for CloudX publishers.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed (private company)
- **Key Metric**: Total funding of **$30.1M** (Series A, raised in November 2025)
- **Notable Investors/Partners**: Lead investor: **Addition** (Series A, 6 investors total). Key partnerships include DT (demand source).
- **Growth Signals**:
  - Headcount: 36 employees (as of mid-2026), with a **monthly growth rate of +5.1%**.
  - Distributed workforce across 11 countries (US, UK, Singapore, Kyrgyzstan, Cyprus, Ukraine, Switzerland, North Macedonia, Slovenia, Argentina, and more).
  - Active hiring across technical and business roles (Senior ML Engineer, Senior Fullstack Engineer, Forward Deployed Engineer, Business Development, etc.).
  - Recent product launches: CloudX Agent (July 2026), Total Revenue dashboard (August 2026), DT SDK Bidder (August 2026).

## Competitive Advantages
- **Founding team pedigree**: Built by the creators of **MoPub** and **MAX**—two transformative mobile ad platforms. This deep industry expertise gives them a unique understanding of publisher pain points.
- **TEE (Trusted Execution Environment) infrastructure**: Provides transparency, data integrity, and security for AI-driven ad auctions—a strong differentiator in a privacy-conscious era.
- **AI-native architecture**: Built from the ground up for AI, not retrofitted. Enables adaptive optimization, real-time intelligence, and support for generative/agentic environments.
- **Publisher-first approach**: Focus on empowering mobile publishers with control, transparency, and modern tools.

## Strategic Focus
- Expanding globally with the first dedicated BD hires in Turkey (a mobile gaming powerhouse) and growing the EMEA business.
- Scaling the engineering team to build out the AI-native platform, including the CloudX Agent and infrastructure for high-throughput, low-latency ad serving.
- Building out demand sources (e.g., DT SDK Bidder) to increase publisher revenue.
- Deepening multi-platform reporting and analytics capabilities.

## Why Work Here
- **Small, senior team**: CloudX emphasizes a "small, senior team" where engineers "own real surface area from day one." The average seniority skews towards experienced professionals (37% Specialist, 17% Head, 5% C-Level/Founder).
- **Remote & hybrid flexibility**: Roles are listed as "In-Office or Remote" with 7–37 locations depending on the role. The website notes "OnSite Workspace" but employees are distributed across 11 countries, indicating strong remote support.
- **Engineering culture**: Cutting-edge tech stack (AI, TEE, high-throughput systems). Blog posts detail architecture decisions (e.g., building an in-house sandbox platform for the Agent).
- **Perks & environment**: Fast-paced startup environment with a focus on ownership and impact. Alumni talent sources include Apple, Roblox, AssemblyAI, and Publicis Groupe.
- **Recent hiring push**: As of August 2026, CloudX is actively hiring for technical roles (Senior ML Engineer, Senior Data Engineer, Senior Fullstack, Senior Infrastructure Engineer, Senior Android SDK Engineer, Quality Engineer) and business roles (Business Development, Partner Success, Revenue Analytics).

## Sources
1. [cloudx.ai](https://www.cloudx.ai/careers) – Careers page (description, roles)
2. [linkedin.com](https://www.linkedin.com/company/cloudxinc) – Company overview, financials, headcount, locations, recent posts
3. [builtin.com](https://builtin.com/company/cloudx) – Company profile, office locations, founding year
4. [builtinsf.com](https://www.builtinsf.com/company/cloudx/jobs) – Job listings, details on roles and culture

## Other roles at CloudX

- [Partner Success (Vietnamese Speaker)](https://feeny.ai/job/partner-success-vietnamese-speaker-cloudx-apac-yhjc4g8g9z57) — APAC
- [Partner Success, EMEA](https://feeny.ai/job/partner-success-emea-cloudx-emea-60bfb6c95mdb) — EMEA
- [Revenue Operations](https://feeny.ai/job/revenue-operations-cloudx-global-ptw12s9v3mx2) — Global
- [Quality Engineer](https://feeny.ai/job/quality-engineer-cloudx-global-xvn9b70pqckn) — Global
- [Business Development, EMEA](https://feeny.ai/job/business-development-emea-cloudx-emea-x26w5e2a4a7t) — EMEA
- [Forward Deployed Engineer (EMEA)](https://feeny.ai/job/forward-deployed-engineer-emea-cloudx-global-1cbag5c9f64j) — Global
- [Senior iOS SDK Engineer](https://feeny.ai/job/senior-ios-sdk-engineer-cloudx-global-8nsa3sjrf4jt) — Global
- [Senior Android SDK Engineer](https://feeny.ai/job/senior-android-sdk-engineer-cloudx-global-5yyfewarynj6) — Global
- [Senior Infrastructure Engineer](https://feeny.ai/job/senior-infrastructure-engineer-cloudx-global-ee5dpedjd01d) — Global
- [Senior Fullstack Engineer](https://feeny.ai/job/senior-fullstack-engineer-cloudx-global-0a82943y6q8k) — Global