Senior ML / Data Engineer - Applied AI
Adikteev
About the role
About the Role
We are looking for a Senior Machine Learning / Data Engineer to join our team.
This role can be based in Barcelona or Paris on a hybrid schedule, or fully remote from anywhere else within the European Union.
Who We Are
Adikteev fuels the app ecosystem by inspiring users to engage with the apps they know and love. Specializing in user retention, we grow in‑app revenue and build user loyalty with custom retargeting and CTV campaigns.
Operating globally from Barcelona, Paris, San Francisco, and Seoul, Adikteev has grown to over 100 employees and achieved 60% revenue growth this year.
What You Will Do
- Take ownership of our ML Platform, designing, deploying, and evolving predictive models that power Adikteev's core adtech systems.
- Architect the infrastructure that enables our ML models to scale, perform, and deliver value at high velocity.
- Join a high‑performing team alongside Gwennaëlle, Nicolas, Pedro, and Alex to deliver efficient, scalable, and impactful machine learning systems that influence billions of real‑time decisions per day.
- Shape our technical DNA and address the following challenges:
- Architect, scale, and maintain our data infrastructure for real‑time and batch ML workflows.
- Build and maintain ML models focused on maximizing return‑on‑investment for every ad impression while meeting production constraints (large volumes, low latencies).
- Design and implement our feature store to centralize feature discovery, storage, and serving, and build robust feature engineering pipelines.
- Build and optimize highly scalable pipelines using Apache Airflow and Apache Spark, emphasizing reliability and cost‑efficiency.
- Contribute to innovation by exploring recent academic work and turning ideas into production‑grade solutions.
- Leverage AI coding tools (Copilot, Cursor, etc.) to accelerate development cycles and stay at the forefront of engineering productivity.
- Drive best practices for data quality, CI/CD for data, and technical documentation; mentor peers and identify infrastructure bottlenecks before they impact the business.
Who You Are
You might be a great fit for our Machine Learning team if you have experience in several of the following areas (don’t worry if you don’t check every box; we consider strong candidates eager to learn and grow):
- Experience: Proven track record as a Machine Learning Engineer, ideally with a focus on data engineering, MLOps, and production‑related challenges (latency, throughput, server cost optimization…).
- Technical Stack: Hands‑on expertise with Apache Spark (tuning, scaling) and Airflow (complex DAG orchestration). Kafka streaming and Kubernetes are a plus. Our stack runs on AWS, so knowledge of this platform is also a plus.
- Coding Skills: Strong proficiency in Python or Scala/Java. You are an “AI‑native” developer who embraces AI tools to write better, faster code.
- Data Modeling: Experience with tabular data for classification and regression problems; experience with deep learning.
- Feature Engineering: Solid understanding of transforming raw data into high‑quality features for machine learning; experience building or maintaining feature stores.
- Mindset: A “Product Owner” mentality for data—you don’t just ship code; you own the reliability and scalability of the systems you build.
- Communication: Fluent in English and able to articulate complex architectural choices to both technical and non‑technical stakeholders. Notions of French can be a plus.
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.
Perks and Benefits
- Competitive Salary
- 4 ½ day work week (Fridays afternoon off)
- Performance‑based Quarterly bonus with transparent KPIs
- Profit‑sharing scheme (“Prime de participation”)
- Longevity bonus every 2 years
- Healthcare plan with excellent coverage
- €9 Lunch Vouchers (Tickets Restaurant – SWILE card – 50 % of the contribution covered by Adikteev)
- “RTT”
- Mental Health support
- Flexible remote working policy
- Regular team‑life events / activities
- 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 Mélanie, Talent Acquisition Partner
- A 1‑hour technical interview with Gwennaëlle, Staff Machine Learning Engineer, and Youcef, Senior Engineering Team Lead
- A 1‑hour team‑fit + system design interview with Julien, Machine Learning Team Lead, and 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, supportive 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.
Requirements
- Proven track record as a machine learning Engineer, ideally with a focus on data engineering, MLOps and production-related challenges (latency, throughput, server cost optimization...).
- Hands-on expertise with Apache Spark (tuning, scaling), Airflow (complex DAG orchestration).
- Strong proficiency in Python or Scala/Java.
- Experience with tabular data for classification and regression problems.
- Experience of deep learning.
- Solid understanding of how to transform raw data into high-quality features for machine learning.
- Experience building or maintaining feature stores.
- A "Product Owner" mentality for data, you don't just ship code; you own the reliability and scalability of the systems you build.
- Fluent in English and the ability to articulate complex architectural choices to both technical and non-technical stakeholders.
Responsibilities
- Architect, scale, and maintain our data infrastructure, ensuring it meets the rigorous demands of real-time and batch ML workflows.
- Build and maintain ML models focused on getting the best return-on-investment for every ad impression while satisfying production constraints specific to our industry (large volumes and low latencies).
- Design and implement our feature store to centralize feature discovery, storage, and serving and build robust feature engineering pipelines.
- Build and optimize highly scalable pipelines using Apache Airflow and Apache Spark, focusing on high reliability and cost-efficiency.
- Contribute to innovation efforts, by exploring promising ideas from recent academic work and turning them into production-grade solutions.
- Leverage AI coding tools (Copilot, Cursor, etc.) to accelerate development cycles and stay at the forefront of engineering productivity.
- Drive best practices for data quality, CI/CD for data, and technical documentation.
- Mentor peers and identify infrastructure bottlenecks before they impact the business.
Benefits
Skills
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