ML Team Lead — Real-Time AdTech (Remote, 4.5‑Day Week)

Adikteev; Paris; Hybride; EUR 130 000 - 150 000; Plein temps

Avantages offerts par ce poste

Competitive salary

Quarterly bonus with KPIs

Longevity bonus every 2 years

4.5-day workweek

RTT

Mental health support

Flexible remote policy

Team-life events

Inclusive parental leave

Résumé du poste

Adikteev, a leading AdTech company, is looking for a Machine Learning Team Lead to guide the ML engineers and own the ML ecosystem at scale. You will steer model development for CTR/CR/LTV, advance our ML platform and ensure sub-10ms inference while coordinating with cross-functional teams.

You will also mentor the team, drive production-grade ML practices, and lead R&D from prototype to production in a fast-growing, inclusive environment.

Qualifications

• 8+ years of industry ML engineering experience with 3+ years in a technical leadership role.
• Hands-on DSP experience in programmatic advertising and RTB.
• Strong ML stack knowledge and production-grade coding practices.

Responsabilités

• Lead, grow, and mentor the ML team, setting technical direction.
• Design and train predictive models for CTR, CR, VTA, and bidding.
• Scale ML platform, feature stores, pipelines, and A/B experiments.
• Drive sub-10ms real-time inference and low-latency serving.
• Own end-to-end MLOps: data ingestion to monitoring and retraining.

Connaissances

ML team leadership

DSP background

Recommender systems

LTV modeling

Python

PyTorch or TensorFlow

scikit-learn

MLflow / Weights & Biases

Spark or Flink

Production-grade software

Clear communication

Outils

PyTorch

TensorFlow

scikit-learn

MLflow

Weights & Biases

Spark

ONNX

Description du poste

Adikteev, a leading AdTech company, is looking for a Machine Learning Team Lead to guide the ML engineers and own the ML ecosystem at scale. You will steer model development for CTR/CR/LTV, advance our ML platform and ensure sub-10ms inference while coordinating with cross-functional teams.

You will also mentor the team, drive production-grade ML practices, and lead R&D from prototype to production in a fast-growing, inclusive environment.