WHO WE ARE

Adikteev is an AdTech company that helps mobile app publishers grow their revenue through targeted advertising. We deliver personalized ads that drive users to install an app or re-engage with one they've stopped using.

Our clients are mostly mobile gaming leaders but also span e-commerce, on-demand services, and entertainment apps. Recognized for 10+ years as one of the top mobile retargeting platforms, Adikteev now operates globally from Paris, San Francisco, Barcelona and Seoul and has grown to over 120 employees.

Beyond the business, Adikteev is consistently recognized as a great place to work. With an 18-nationality team, a 4.5-day work week, and a strong focus on inclusion, Adikteev is a place where people genuinely stay.

WHAT YOU WILL DO

Every model our ML team ships lives or dies on the infrastructure underneath it. We're looking for a Senior Data Engineer who thinks like a machine learning practitioner, not just a pipeline builder, to own the platform that turns raw data into features, features into models, and models into billions of real-time decisions per day.

- Own the Infrastructure That Powers Prediction

Architect, scale, and maintain the data infrastructure behind our real-time and batch ML workflows, the systems that let CTR, CVR, VTA, and bidding models run at production velocity without breaking.
- Build the Feature Store, Not Just the Pipeline

Design and implement a feature store that centralizes feature discovery, storage, and serving. This is the foundation every model on the team will build on, and you'll be the one deciding how it's structured.
- Engineer for ML Reliability, Not Just Data Reliability

Streamline data processes with testing, monitoring, alerting, and error recovery built specifically for the failure modes ML systems create, silent drift, stale features, training/serving skew, not just generic pipeline breakage.
- Scale Pipelines That Feed Models in Production

Build and optimize highly scalable pipelines using Apache Airflow and Apache Spark, with an eye on the reliability and cost-efficiency that production ML demands at high QPS.
- Turn Research Into Production ML Systems

Contribute to innovation efforts by exploring promising ideas from recent ML/academic work and turning them into production-grade infrastructure, not proofs of concept that die in a notebook.
- Move Fast With AI-Native Engineering

Leverage AI coding tools (Copilot, Cursor, etc.) to accelerate development and stay ahead on engineering productivity, so more of your time goes to the hard ML infrastructure problems.
- Set the Bar for Data-for-ML Practices





Drive best practices for data quality and CI/CD tailored to ML pipelines (schema validation, feature drift checks, reproducibility). Mentor peers, and catch infrastructure bottlenecks before they become model-performance problems.

WHO YOU ARE

You'd be a great fit for our Machine Learning team if you have experience in several of the following:

- Experience: A proven track record as a Data Engineer, ideally with real MLOps exposure, feature pipelines, model-serving infrastructure, latency/throughput tuning, or the operational challenges specific to keeping ML systems healthy in production.
- ML-Adjacent Technical Stack: Hands-on expertise with Apache Spark (tuning, scaling) and Airflow (complex DAG orchestration) applied to ML workloads. Kafka streaming and Kubernetes are a plus, especially for real-time feature serving. AWS experience is a plus, our stack runs on it.
- Coding Skills: You're an "AI-native" developer who uses AI tools to write better, faster code. Python is core; Java/Scala is a plus.
- Feature Engineering Depth: Solid understanding of how to transform raw data into high-quality features for ML, including experience building or maintaining feature stores, this is one of the most ML-facing parts of the role.
- Data Modeling Curiosity: Exposure to tabular data for classification problems and/or deep learning is a plus. You don't need to train models yourself, but you should understand what the models you're feeding actually need.
- Mindset: A "Product Owner" mentality for data. You don't just ship pipelines, you own the reliability and scalability of the systems that ML models depend on.
- Communication: Fluent in English, with the ability to translate architectural choices for both engineers and ML practitioners.

Please note that, to comply with employment regulations, applicants are required to maintain residency and be legally authorized to work in the European Union in order to be considered for this position.

COMPENSATION

- Competitive Salary between 80,000 and 90,000€ OTE

We are committed to transparent compensation practices. The salary range shown reflects total On-Target Earnings (OTE), including base salary and a performance-based Quarterly bonus with transparent KPIs.



Final compensation will be tailored to each candidate’s background, experience, skills, and overall fit for the role.

PERKS AND BENEFITS

- 4 1/2 days work week (Fridays afternoon off);
- Longevity bonus every 2 years;
- Healthcare plan with excellent coverage;
- Lunch Vouchers;
- Mental Health support;
- Adaptable remote working policy;
- Regular team-life event / activity;
- Inclusive parental leave Policy.

*Most benefits are available to all employees. For remote team members based outside of France, benefits will be aligned with local laws and practices in your country of residence, ensuring support that’s both relevant and compliant wherever you are.

OUR PROCESS

What to expect as you move through our hiring process:

- A HR call with Claire, Senior Talent Acquisition Partner,
- A 1h technical interview with a Senior Machine Learning Engineer and a member of our Data Engineering team,
- A 1h team fit interview with Aldenis, VP Engineering,
- A final interview with Cédric, Chief Technology Officer and Loïc, Chief Product Officer.

If you require accommodations at any stage of the application process, please let us know. It will be handled confidentially by our HR and recruitment team.

HOW WE MAKE AN IMPACT

Own it, Live it: Our top priority is making sure our customers are fully supported and engaged. We're not afraid to make decisive moves, embrace challenges, and see them through to the end.

Rolling with Changes: We don't just face challenges, we anticipate them. Agility is core to who we are, and we believe in continuous learning and improvement.

Making waves with purpose: We're here to make a difference. Every decision and action is aimed at creating a positive and meaningful impact.

The ADIKTEAM vibe: We're more than a team; we're the ADIKTEAM. Everyone plays a crucial role, and we're always looking for people who thrive in collaborative, supporting environments.

OUR COMMITMENT

We’re proud that our team already spans 22+ nationalities, diverse talent and unique backgrounds, and we want it to grow even more. If this role appeals to you, we welcome your application, even if you don’t meet every single qualification. Not everyone gets through our hiring process, but your skills might be a great fit for another opportunity; now or in the future.

Adikteev is an equal opportunity employer. We are committed to building an inclusive environment for all employees, candidates, vendors and clients, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, age, national origin, disability, marital status, or military status.

📌 Senior Data Engineer (Machine Learning focus) (Barcelona)
🏢 Adikteev
📍 Barcelona