Principal ML Platform Engineer - Real-Time AI & Infra

DAT Freight & Analytics; Seattle (WA); On-site; USD 257,000 - 321,000; Full time

Benefits offered by this job

Medical, Dental, Vision insurance

Parental Leave

Flexible Vacation Time

401k matching

Employee Stock Purchase Plan

Transit assistance

Job summary

DAT Freight & Analytics seeks a Principal Software Engineer, ML Platform to lead the evolution of its ML platform. You will manage a 3–4 member team, set technical direction, and partner with scientists and product engineers to accelerate iteration and innovation.

You will own core capabilities for low-latency feature stores, real-time streaming, and robust DevOps/MLOps foundations, enabling production-grade ML across the DAT marketplace.

Qualifications

• Extensive ML engineering and data infrastructure experience.
• Hands-on with real-time ML platforms, feature stores, and online inference.
• Strong Python, plus familiarity with TypeScript/Node and Kubernetes.
• Experience with modern data/ML infra: Kafka, Kubernetes, cloud platforms.
• Leadership: mentor a small engineering team while contributing technically.

Responsibilities

• Lead the technical direction for the ML platform and manage a 3-4 member team.
• Mentor engineers and scientists; deliver scalable ML/AI solutions.
• Define durable service patterns for API design, deployment, monitoring.
• Lead experimentation and evaluation infrastructure development.
• Scale platform capabilities with cross-team collaboration.

Skills

ML platform engineering

Platform leadership

Python

TypeScript/Node

DevOps & MLOps

Experimentation tooling

Tools

Kubernetes

Kafka

Terraform

Snowflake

dbt

PostgreSQL

Job description

DAT Freight & Analytics seeks a Principal Software Engineer, ML Platform to lead the evolution of its ML platform. You will manage a 3–4 member team, set technical direction, and partner with scientists and product engineers to accelerate iteration and innovation.

You will own core capabilities for low-latency feature stores, real-time streaming, and robust DevOps/MLOps foundations, enabling production-grade ML across the DAT marketplace.