Machine Learning Engineer, Outmax

pythonmachine learningstatisticsml pipelinesapiadtechDSPSSPMCPLangChaindata science

Key details

Salary

Not specified

Employment type

Full-time

Seniority

Senior

Years experience

3-5

Location

Paris, France

Full job description

Perion is a global adtech company delivering AI/ML-based solutions across multiple platforms. The ML Engineer role at Outmax, based in Montpellier or Paris with flexible remote options, involves building and deploying bid optimization ML pipelines, designing statistical frameworks to improve campaign KPIs, developing backend services exposing ML model outputs via API, wiring MCP servers for new data sources, and owning features end-to-end. Requirements include 3+ years experience in machine learning, data science or backend engineering, strong Python skills, solid statistics and ML knowledge, ability to own features from design to production, and proficiency in English. Nice to have experience with adtech platforms (DSPs, SSPs) and agentic AI frameworks like MCP or LangChain.

What you'll do

Build and deploy bid optimisation ML pipelines that feed directly into ad buying platforms, owning the full lifecycle from design to production
Design statistical frameworks to evaluate and improve campaign KPI performance for brand and agency clients
Develop production-grade backend services to expose ML model outputs via API, writing clean, reliable code
Wire MCP servers to extend Outmax's agentic offering with new data sources and actions
Own features end-to-end, from ideation and scoping through to deployment and iteration

Requirements

3+ years of experience combining machine learning, data science, or backend engineering at an intermediate to senior level
Strong Python skills with the ability to write clean, production-ready code
Solid grounding in statistics and ML, including model building, evaluation, and pipeline design
Proven ability to own features end-to-end, from design through to production deployment, in a small team environment
Proficiency in English, both written and verbal