Machine Learning Team Manager/Director

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 TEAM YOU WILL BE PART OF

You will be joining as Director of Machine Learning / Machine Learning Team Manager, leading our Machine Learning team. This team has full ownership of Adikteev's ML ecosystem, building and maintaining the systems that power the core of our business at massive scale. They operate with a strong product ownership mindset, working at the intersection of research and production, where the models they ship have a direct and measurable impact on billions of real-time decisions every day.

WHAT YOU WILL DO

• Team Leadership: Lead, grow, and manage the Machine Learning team, setting technical direction and priorities while directly managing and mentoring ML engineers, including senior profiles.

• Model Development: Design and train predictive models for CTR, CR, VTA, bid shading, and auction-win probability across display and video inventory.

• Platform Engineering: Scale our ML platform, feature stores, training pipelines, model versioning, A/B experimentation, to support multiple model families running in production simultaneously.

• Real-time Systems: Drive sub-10ms inference at high QPS through model optimization (ONNX), efficient serving, and latency-aware architecture decisions, informed by hands-on DSP/RTB experience.

• MLOps & Observability: Own end-to-end ML workflows from data ingestion through monitoring: drift detection, shadow scoring, A/B tests, and automated retraining triggers; drive design reviews, ADRs, and mentoring of the team. Translate business objectives into technical strategies.

• Cross-functional Partnership: Work closely with Tech, Reporting, Product and Analytics teams to define ML KPIs, instrument experiments, and communicate model performance to stakeholders up to Comex level.

• Applied Research: Design and set up a neural network for adtech from the ground up, taking it from prototype to production in our bidding stack.

★ WHO YOU ARE

You could be a great addition to our Engineering team as Director of Machine Learning if you have:

• 8 years of industry ML engineering experience, with 3 years in a technical leadership or team lead role, owning production ML systems at scale.

• Required DSP background: hands-on experience building and operating ML systems within a DSP (Demand-Side Platform) environment is mandatory, including deep familiarity with programmatic advertising, RTB, mobile attribution (MMP ecosystem, SKAdNetwork, Privacy Sandbox), and bidding infrastructure.

• Deep expertise in recommender systems and/or LTV/churn modeling within an adtech context.

• Strong command of the modern ML stack: Python, PyTorch or TensorFlow, scikit-learn, MLflow or Weights & Biases, Spark or Flink for feature engineering.

• Solid software engineering fundamentals, you write production-grade, reviewable code and care about system reliability.

• Proven experience leading or mentoring a team of ML engineers, with the ability to set technical vision while remaining hands-on.

• Track record of delivering value incrementally, shipping working software in small, frequent increments rather than large