Machine Learning Data Infrastructure Engineer

Job overview

The Machine Learning Data Infrastructure Engineer role is hybrid in San Mateo, CA, with three days in the office (Monday–Wednesday) and two optional remote days (Thursday–Friday). The salary is $175,000–$225,000 annually, plus equity. Cognitiv develops a deep-learning advertising platform to improve the precision and impact of digital advertising. The engineer builds and evolves scalable feature and model-training infrastructure that supports real-time bidding and advertising models. The role improves pipeline performance, reliability, and serving latency while partnering with engineering, product, and data science teams.

What you'll do

• Architect and maintain batch, streaming, and historical feature pipelines
• integrate embeddings into feature storage and serving systems
• optimize model-training pipelines
• establish monitoring, testing, and CI/CD standards
• collaborate with modeling and data science teams to deliver production-ready features
• improve system reliability, scalability, and efficiency.

What we're looking for

Skills & competencies

machine learning infrastructure

data platform

feature pipelines

distributed systems

adtech

python

java

kafka

flink

spark

san mateo ca

hybrid

$175k–$225k/year

equity

Work arrangement

• Weekend coverage required

Benefits & perks

• Equity
• medical, dental, and vision plans
• paid parental leave
• unlimited paid time off
• work-from-anywhere August
• 401(k) match
• wellness stipend
• commuter benefits
• employee assistance program.

Why this role

Senior individual-contributor role focused on large-scale machine-learning infrastructure, feature pipelines, and model training.

About the employer

Cognitiv is hiring for this role. Industry: Software Publishers. Sector: 51.