Senior MLOps Engineer — Build Scalable AI Pipelines

Glocomms; California (MO); Hybrid; USD 198,000 - 230,000; Full time

Benefits offered by this job

Meal stipends for remote work days

Generous paid time off

Comprehensive health coverage

Retirement savings plan options

Job summary

A rapidly growing technology company in California is seeking a Senior MLOps Engineer to lead technical initiatives for applied AI with a focus on model evaluation and annotation workflows. You will work in a hybrid environment that encourages innovation and individual work styles. Applicants should have extensive experience in MLOps, strong Python skills, and a collaborative mindset. This position offers generous health and financial benefits, as well as professional development opportunities.

Qualifications

• Experience building and managing annotation workflows using commercial or custom tools.
• Hands-on experience with model monitoring and production ML infrastructure.
• Strong Python skills for building integrations and pipelines.
• Experience in cloud ML environments, preferably AWS or GCP.
• Comfortable collaborating with DevOps/SRE teams.

Responsibilities

• Architect annotation and measurement pipelines to support ground-truth generation.
• Drive cost-efficient model evaluation and create ground-truth datasets.
• Implement frameworks for deterministic preprocessing and model evaluation.
• Collaborate with Data Science to drive applied generative AI decisions.
• Integrate measurement and evaluation loops into the broader cloud ecosystem.

Skills

Annotation & Evaluation Expertise

Applied MLOps Practitioner

Technical Proficiency

Cloud & Infrastructure Fluency

Collaborative Technical Leader

Tools

Python

AWS

GCP

Job description

A rapidly growing technology company in California is seeking a Senior MLOps Engineer to lead technical initiatives for applied AI with a focus on model evaluation and annotation workflows. You will work in a hybrid environment that encourages innovation and individual work styles. Applicants should have extensive experience in MLOps, strong Python skills, and a collaborative mindset. This position offers generous health and financial benefits, as well as professional development opportunities.