Senior Machine Learning Engineer - Applied AI
Role details
Job location
Tech stack
Job description
We are looking for a Senior Machine Learning Engineer to take ownership of our ML Platform. You will help design, deploy, and evolve predictive models that power Adikteev's core adtech systems and you will be the architect of the infrastructure that enables our ML models to scale, perform, and deliver value at high velocity.
You will join a high-performing team alongside Gwennaëlle, Nicolas, Pedro, and Alex. Our mission is to deliver efficient, scalable, and impactful machine learning systems - models that directly influence billions of real-time decisions per day.
You will join a team that has full ownership of our ML ecosystem. As a Senior member, you won't just "execute" tasks. You will shape our technical DNA and take your share of the following challenges:
- 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., * A 1h technical interview with Gwennaëlle, Staff Machine Learning Engineer and Youcef, Senior Engineering Team Lead,
- A 1h 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.
Requirements
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're happy to consider strong candidates who are 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), Airflow (complex DAG orchestration). Kafka streaming and Kubernetes are a plus. Our stack runs on AWS so a good 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 of deep learning.
- Feature Engineering: Solid understanding of how to transform 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 the ability 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.
Benefits & conditions
-
Competitive Salary;
-
4 1/2 days 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 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.