Senior ML Data Platform Engineer (Hybrid)

Cognitiv; San Mateo; Hybrid; PHP 11,034,000 - 14,187,000; Full time

Benefits offered by this job

Medical, Dental and Vision plan for US

Extended Health Benefits for Canadian

12 weeks paid parental leave

4 weeks WFH

Unlimited PTO

Work-From-Anywhere August

Career development

Equity for all employees

Hybrid work model

Daily team lunch

Health & wellness stipend

cell phone reimbursement

401(k) & RRSP with employer match

Employee Assistance Program

Job summary

Cognitiv, a leader in AI-driven advertising, seeks a senior ML Infrastructure engineer to own feature pipelines and training systems at our San Mateo, CA location with a hybrid schedule (3 days in office, 2 remote). You will work at scale across data platforms and platform architecture, delivering low-latency pipelines and reliable training processes.

Join a team partnering with modeling, data science, and infrastructure to push the boundaries of real-time bidding, embeddings, and AI

Qualifications

• Irrefutable 3–5+ years of hands-on ML infrastructure experience.

Responsibilities

• Architect, build, and maintain low-latency feature pipelines (batch, streaming, and point-in-time features).
• Leverage embeddings and AI models to enrich core feature store and serving system.
• Own and enhance ad model training pipelines for speed and throughput.
• Set up monitoring, testing, and CI/CD for feature and training infra.
• Collaborate with Modeling & Data Science to boost model performance.

Skills

ML Infra

Data Platform

Pipelines

Python/Java/Scala

Spark/Flink/Kafka

Communication

Tools

PyTorch

AWS/GCP

Kubernetes

Docker

Job description

Cognitiv, a leader in AI-driven advertising, seeks a senior ML Infrastructure engineer to own feature pipelines and training systems at our San Mateo, CA location with a hybrid schedule (3 days in office, 2 remote). You will work at scale across data platforms and platform architecture, delivering low-latency pipelines and reliable training processes.

Join a team partnering with modeling, data science, and infrastructure to push the boundaries of real-time bidding, embeddings, and AI