ML engineer in adtech

Adikteev; United States; Remote; USD 141,000 - 169,000; Full time

Benefits offered by this job

Flexible remote work

Mental health support

Longevity bonus every 2 years

4.5 day work week (Fridays afternoon)

Job summary

Adikteev ищет старшего ML-инженера с опытом разработки и эксплуатации масштабируемых ML-систем в рекламном тех стеке. Вы будете формировать техническую стратегию, проектировать прогнозирующие модели и руководить командами инженеров.

Основной фокус — создание и развёртывание ML-решений в реальном времени с низкой задержкой, работа с фреймворками PyTorch/TensorFlow и инструментами мониторинга. Глобальное присутствие, конкурентные компенсации и гибкая удалённая работа.

Qualifications

• 8+ лет опыта в ML-инженерии.
• 3+ лет внедрения production ML-систем в масштабе.
• Опыт в прогрессивной рекламе / AdTech обязателен.

Responsibilities

• Задавать техническое направление ML-инициатив.
• Проектировать и обучать предиктивные модели для CTR/CR/VTA и ставок.
• Обеспечивать суб-10мс инференс и низкую задержку сервисов.

Skills

Python

PyTorch

TensorFlow

Scikit-learn

MLflow/Weights & Biases

Spark/Flink

API/ML serving

Tools

ONNX

Triton

TorchServe

Job description

Описание:

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.

Задачи:

Set technical direction Design and train on predictive models for CTR, CR, VTA, bid shading, and auction-win probability across display and video inventory Scale our ML platform — feature stores, training pipelines, model versioning, A/B experimentation — to support multiple model families running in production simultaneously Drive sub-10ms inference at high QPS through model optimization (ONNX), efficient serving, and latency-aware architecture decisions 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 senior+ ML engineers Translate business objectives into technical strategies Work closely with Tech Reporting and Analytics to define ML KPIs, instrument experiments, and communicate model performance to stakeholders up to Comex level Design and set up a neural network for adtech from the ground up, taking it from prototype to production in our bidding stack

Требования:

8+ years of industry ML engineering experience, with 3+ years building and owning production ML systems at scale. Hands-on adtech experience is required — programmatic advertising (RTB/DSP), mobile attribution (MMP ecosystem, SKAdNetwork, Privacy Sandbox), or real-time bidding — alongside deep expertise in recommender systems and/or LTV/churn modeling. Strong command of the modern ML stack: Python, PyTorch or TensorFlow, scikit-learn, MLflow or Weights & Biases, Spark or Flink for feature engineering. Experience with real-time serving infrastructure: Triton, TorchServe, Ray Serve, or custom low-latency gRPC services. Solid software engineering fundamentals — you write production-grade, reviewable code and care about system reliability. Track record of delivering value incrementally — shipping working software in small, frequent increments rather than large multi-quarter projects. Clear, concise communicator who can translate model performance into business impact for non-technical audiences. applicants are required to maintain residency and be legally authorized to work in France or the European Union in order to be considered for this position.

Условия:

Competitive Salary between 125,000€ and 150,000€ OTE 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 Performance-based Quarterly bonus with transparent KPIs Longevity bonus every 2 years 4 1/2 days work week (Fridays afternoon off) RTT Mental Health support Flexible remote working policy Regular team-life event / activity Inclusive parental leave Policy