---
title: 'Senior ML Engineer - Offline Team at Voodoo'
canonical: 'https://feeny.ai/job/senior-ml-engineer-offline-team-voodoo-helsinki-fcgwq2hh11hn'
type: 'job'
last_seen: '2026-09-08'
---

# Senior ML Engineer - Offline Team at Voodoo 

- **Company:** [Voodoo ](https://feeny.ai/companies/voodoo)
- **Location:** Helsinki, Finland
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-18
- **Last confirmed live:** 2026-09-08
- **Apply:** https://jobs.ashbyhq.com/voodoo/c16d0de3-e5b7-4fb9-ae0e-a906a75e9b15/application

**Skills:** Python, Scikit-learn, LightGBM, PyTorch, Deep Learning, Amazon Web Services, DBT, Spark, MLflow, Prometheus, Terraform, Airflow, Kubernetes, ML Training Lifecycle, Experiment Management, Cloud Infrastructure, Model Serving, Real-time Inference, Batch Inference, Latency Optimization

> The Senior ML Engineer will lead the architecture and maintenance of ML training infrastructure for ad-targeting models, spanning data preprocessing to production deployment. Responsibilities include optimizing data pipelines, enabling data scientists with reusable components, and managing deep learning workloads on...

## Job description

## ABOUT VOODOO

Founded in 2013, Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees, 7 billion downloads, and over 200 million active users, Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes chart-topping games like Mob Control and Block Jam, alongside popular apps such as BeReal and Wizz.

## TEAM

The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile gaming industry.

The Voodoo Ad-Network is an autonomous product group of around 60 highly driven professionals with an ambitious mission: building top-tier ad network services. Our primary goal is to leverage Voodoo's massive first-party data ecosystem to optimize and scale monetization. We are in a rapid growth phase, expanding into new ventures such as opening to external inventory, penetrating the external advertiser market, and driving social network monetization following our recent acquisition of BeReal. To support this incredible trajectory and promising early results, we are scaling our team.

The Models team is a core element of the targeting performance. It leverages machine learning and a strong business understanding to directly impact the product's financial performance. It's composed of mostly senior Data Analysts, Analytics Engineers, Data Engineers and Data Scientists/ML Engineers that iterate together on finding and building the next performing iteration.

This role can be either Paris or Helsinki based and done in a hybrid setup.

## ROLE

We're looking for a Senior ML Engineer to join our Models team. You will be joining a dedicated squad of Data Engineers, Data Scientists, and ML Engineers focused on building and maintaining the ML training infrastructure that powers our ad-targeting models from data preprocessing through model deployment to production monitoring.

In this role, you will be leading the following topics:

- Architectural Ownership: Take end-to-end ownership of highly visible projects from ideation to production release. This includes feature scoping, timeline estimation, architecture design, and benchmarking new technologies.
- Pipeline Engineering: Build and maintain quality data and ML pipelines to align with ever-evolving business and machine learning needs. Optimize training pipelines for performance, memory efficiency, and cost (e.g. spot instance strategies, efficient data loading, preprocessed artifact reuse).
- Data Scientists Enablement: Enable Data Scientists to iterate faster by providing reusable, well-tested pipeline components (transformers, dataloaders, training utilities) and reviewing their contributions to shared code. Extend dataset capabilities: integrating new data sources, scaling feature windows, and increasing training data volumes without breaking pipeline constraints.
- Deep Learning Development: Contribute to deep learning development: GPU workload orchestration, custom PyTorch training loops, and model architecture support.
- ML Lifecycle & Reproducibility: Maintain reproducibility and consistency across the ML lifecycle: versioned configs, experiment tracking, and online-offline consistency tooling.
- Scalability & Reliability: Collaborate with infrastructure teams on scalability — node pools, resource monitoring, CI/CD migrations. Participate in weekly rotation to triage and resolve alerts from Airflow, dbt, and related systems.
- Agile Collaboration: Thrive in a fast-paced agile environment with rapid decision-making processes. You will collaborate daily with back-end developers, data scientists, infrastructure engineers, and product managers.
- Mentorship & Team Culture: You will actively contribute to our engineering culture, share knowledge, and ensure every team member feels comfortable, supported, and empowered to grow in their role.

## PROFILE

We are looking for a Senior ML Engineer who deeply understands both the ML training lifecycle and the specific challenges of putting machine learning models into production at scale.

- 5+ years minimum of experience as an ML Engineer or a similar role
- End-to-End ML Ownership: Problem framing, baselines, experimentation, deployment, and iteration
- Python Proficiency: Extensive knowledge for ML pipeline code: preprocessing, training/evaluation workflows, experiment utilities, and reproducible configs
- Training Mechanics: Comfortable implementing training mechanics where needed (custom steps/metrics, dataloading patterns, performance-conscious preprocessing), not only notebook-level prototyping
- ML Frameworks: Practical experience training and evaluating models with scikit-learn, LightGBM, PyTorch for deep learning
- Performance Optimization: Experience optimizing memory usage during data preprocessing and model training
- Experiment Management: Hyperparameter tuning, experiment tracking, and reproducible training (configs, seeds, versioning)
- Cloud & Infrastructure: Experience with Amazon Web Services. Familiarity with scalability, reliability, and security topics
- ML Production Awareness: Understanding of the challenges involved in running ML models in production (familiar with topics such as feature store, training-serving skew, etc.)
- Model Serving: Experience with model serving infrastructure (real-time or batch inference, latency/throughput optimization) is a plus
- Excellent communication skills in English

## OUR STACK

Python · Scikit-learn · LightGBM · PyTorch · DBT · Spark · MLflow · Prometheus · Terraform · Airflow · Kubernetes · Amazon Web Services

## BENEFITS

- Excellent benefits that will depend on the country you're based in

## About Voodoo 

## Company Overview
- **One-liner**: Voodoo is a global tech company that entertains the world through iconic mobile apps and games, empowering bold creators to turn their ideas into hits.
- **Entity Type**: Private (minority stakes from Tencent, Goldman Sachs, and Groupe Bruxelles Lambert)
- **Headquarters**: Paris, France
- **Founded**: 2013
- **Founders**: Alexandre Yazdi, Laurent Ritter

## Core Business
- **Primary industry/industries**: Mobile gaming, mobile apps, social platforms
- **Target customers**: B2C (mobile consumers worldwide)
- **Mission or purpose statement**: "Entertain the world through iconic apps and games" – Voodoo aims to empower bold creators and deliver engaging mobile experiences.

## Products & Services
- **Mob Control**: Hybrid-casual game that grossed nearly $100 million; started as hyper-casual and evolved post-launch.
- **Block Jam 3D**: Block-matching puzzle game; also crossed $100 million in revenue.
- **BeReal**: Photo-sharing social app acquired for €500 million in June 2024; 50 million users globally.
- **Wizz**: Social media platform launched in 2020; 1 million MAU in the US.
- **Publishing Platform**: Voodoo evaluates and publishes games from over 2,000 external studios, providing user acquisition, monetization, and product support.
- **Other notable titles**: Paper.io, Helix Jump, Hole.io, Aquapark.io, Snake vs Block, Baseball Boy.

## Market Standing
- **Valuation/Market Cap**: €1.7 billion (as of August 2021, per Groupe Bruxelles Lambert stake)
- **Key Metric**: Annual revenue of $670 million in 2024 (up from $570 million in 2023)
- **Notable Investors/Partners**: Tencent (minority stake, 2020), Goldman Sachs (minority stake), Groupe Bruxelles Lambert (16% stake, 2021)
- **Growth Signals**:
  - 8 billion total downloads, 150 million monthly active users
  - 20% revenue growth and strong profitability in 2024
  - Acquisition of BeReal for €500M to expand into social apps
  - Headcount grew from ~750 (2023) to 800+ (2024)
  - Opened offices in Singapore, Japan, Istanbul, and Montreal to support global expansion

## Competitive Advantages
- **Data-driven rapid prototyping**: Launches nearly one game per week, testing retention and playtime metrics to iterate quickly.
- **Massive scale and distribution**: 8 billion downloads and a network of 2,000+ external studios give Voodoo unmatched reach in mobile gaming.
- **Successful pivot**: Transitioned from hyper-casual to hybrid-casual games and apps, demonstrating adaptability to market changes.
- **Strong monetization**: In-app purchases and advertising revenue; Mob Control and Block Jam each generated nearly $100 million.

## Strategic Focus
- **Diversification beyond hyper-casual**: Investing in hybrid-casual games and social apps (BeReal, Wizz) to build resilient revenue streams.
- **Asia-Pacific expansion**: Leveraging Tencent partnership and new offices in Singapore and Japan.
- **Continued innovation**: Maintaining a high-velocity testing culture while scaling the publishing platform to attract more external developers.

## Why Work Here
- **Culture**: Values include speed, risk-taking, direct feedback, fighting bureaucracy, high standards, ownership, and long-term thinking. Described as fast-paced and focused on learning quickly.
- **Hiring process**: Aimed at completion within 30 days; includes recruiter conversation, case study/skill test, Q&A, and final interview with senior leadership.
- **Teams**: Growth, Engineering & Data, Gaming, Apps, Strategy & Operations, Corporate.
- **Work environment**: Global offices in Paris (HQ), Istanbul, Montreal, Singapore, and Japan. Remote/hybrid policy not explicitly stated, but roles are likely office-based in key hubs.
- **Notable perks**: Opportunity to work on products with billions of users; ownership mindset encouraged; flat hierarchies with direct feedback culture.

## Sources
1. [voodoo.io](https://voodoo.io/company)
2. [voodoo.io](https://voodoo.io/)
3. [voodoo.io](https://voodoo.io/careers)
4. [en.wikipedia.org](https://en.wikipedia.org/wiki/Voodoo_(company))
5. [linkedin.com](https://www.linkedin.com/company/voodoo.io)

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