Description de posteWe are a global media and tech company that connects people to their passions. We reach nearly 900M people around the world, bringing them closer to what they love—from finance and sports to shopping, gaming and news—with the trusted products, content, and tech that fuel their day.
About the Role We are looking for a
Senior Machine Learning Engineer
to design and scale personalization systems that power contextual ad rendering and recommendation experiences.
This role focuses on building
production-grade, low-latency ML systems
that leverage user signals and smart insights to improve relevance, engagement, and yield—while maintaining strong privacy, security, and compliance standards.
What You'll Do
Design and implement
scalable end-to-end ML systems and infrastructure
for personalization and ranking use cases
Build and optimize classification, ranking, and contextual models
Develop and productionize models with ownership across the full ML lifecycle (training, evaluation, deployment, monitoring)
Build and maintain ML pipelines, feature stores, and model monitoring systems
Optimize ML systems for
low-latency, high-availability production environments
Improve model and system performance (latency, throughput, quantization, pruning, system bottlenecks)
Develop privacy-safe data pipelines and ensure secure handling of sensitive user signals
Support experimentation frameworks (A/B testing) to improve business metrics such as engagement and yield
Partner with cross-functional teams to deliver reliable, scalable ML solutions at scale
Required Qualifications
6+ years of experience in Machine Learning Engineering or ML Systems Engineering
Recent hands-on experience designing and deploying scalable ML systems (within last 12 months)
Strong experience with:
Machine learning algorithms and statistical modeling
Recommendation systems, ranking, or contextual personalization
End-to-end model lifecycle management in production
ML infrastructure, pipelines, and monitoring
Experience optimizing ML inference for performance and scale
Strong programming skills in
Python
(Java is a strong plus)
Hands‑on experience with
TensorFlow
or
PyTorch
Experience with distributed systems, streaming architectures, or high‑availability microservices
Experience with containerization and orchestration tools (Docker, Kubernetes)
Knowledge of CI/CD and infrastructure tools
Nice to Have
Experience with IaC
Experience in AdTech, large-scale consumer platforms, or marketplace systems
Experience operating ML systems in PII-heavy or regulated environments
Familiarity with privacy-preserving ML techniques (tokenization, anonymization, differential privacy)
Experience optimizing models for revenue, CTR, or conversion metrics
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