Data Scientist: ML, Cloud & Network Innovation

Commerce Partners Inc; Fullerton (CA); Hybrid; USD 116,000 - 161,000; Full time

Benefits offered by this job

Paid certifications

Conferences

Dedicated learning time

Job summary

Commerce Partners Inc in Fullerton, CA is hiring a Data Scientist for a hybrid role. You’ll write clean, scalable code, re-architect the flow to handle ten times the current load, surface insights with production data, and help migrate services to the cloud.

Expect to backfill MLOps test coverage and maintain microservices powering our customers. The base salary ranges from $116,000 to $161,000, with opportunities for growth through paid certifications, conferences, and dedicated learning time.

Qualifications

• 5 years of Vertex AI practice, plus a hunger for what's next.
• Confident communicator across email, calls, and in-person meetings.
• Demonstrated wins in technology work somewhere near Fullerton, CA.

Responsibilities

• Write clean, well-tested code that scales with growing users.
• Re-architect technology flow so Networking handles ten times current load.
• Surface insights from production data with data teams.
• Support migration of on-premise services to cloud-native architecture.
• Backfill MLOps test coverage on riskiest code areas.
• Refine and maintain microservices powering customers in Fullerton, CA.
• Own the LangChain subsystem used across the platform.
• Build client-centric Networking features to win CA accounts.

Skills

Vertex AI

MLOps

LangChain

Tools

LangChain

Job description

Commerce Partners Inc in Fullerton, CA is hiring a Data Scientist for a hybrid role. You’ll write clean, scalable code, re-architect the flow to handle ten times the current load, surface insights with production data, and help migrate services to the cloud.

Expect to backfill MLOps test coverage and maintain microservices powering our customers. The base salary ranges from $116,000 to $161,000, with opportunities for growth through paid certifications, conferences, and dedicated learning time.