Senior ML OPs Engineer

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

Overview

Senior MLOps Engineer (Applied AI Focus)

Location: Remote (hybrid available)

Pay: 198K -230K

* Unfortuantely we are unable to provide sponsorship at this time

A rapidly growing technology company is building the operating system for creator‑ and content‑driven growth. The team is driven by a mission to make businesses more human and empower individuals to have greater impact. The culture centers around intentionality, collaboration, continuous improvement, and being a genuinely good human in day‑to‑day work.

The organization has been consistently recognized for excellence across workplace culture, innovation, and product leadership. Team members enjoy a flexible work model that blends in‑person collaboration with remote flexibility, encouraging creativity, connection, and individual work‑style preferences.

We are looking for passionate, forward‑thinking builders to join our journey and help shape the future of our industry.

Role Overview

As a Senior MLOps Engineer on the Product Innovations team, you will serve as the technical lead for Applied MLOps. Your work will bridge the gap between experimental research and production‑ready AI systems, with a strong emphasis on ground‑truth generation, model evaluation, and the pre‑/post‑processing infrastructure that powers large‑scale vector embeddings and applied AI features.

You will play a pivotal role in defining best practices, driving evaluation frameworks, and building the infrastructure that enables experimentation and productionization at scale.

What You'll Do

• Architect Annotation & Measurement Pipelines
• Design and implement human‑in‑the‑loop and automated annotation workflows.
• Build systems for reliable quality metrics, confidence scoring, and inter‑annotator agreement (IAA).
• Stand up annotation tools and processes to support ground‑truth generation at scale.
• Drive Cost‑Efficient Model Evaluation
• Create ground‑truth datasets, golden sets, and model‑by‑model evaluation criteria.
• Benchmark model performance to guide data science decisions and optimize compute and cost efficiency.
• Directly influence product margins by helping deploy the right model for the right use case.
• Enforce Applied MLOps Standards
• Implement frameworks for deterministic preprocessing, PII scrubbing, and model‑as‑a‑judge evaluation loops.
• Establish robust production standards for safety, consistency, and reliability.
• Collaborate on Model & Product Strategy
• Partner closely with Data Science to drive applied generative AI decisions.
• Influence model selection, architecture, and optimization approaches.
• Build & Integrate with Infrastructure
• Work with engineering teams to integrate measurement and evaluation loops into the broader cloud ecosystem (AWS/GCP).
• Ensure automation, observability, and smooth model lifecycle operations.

Who You Are

• Annotation & Evaluation Expertise
  • Experience building and managing annotation workflows using commercial or custom tools.
  • Strong understanding of quality metrics, ground‑truth processes, and IAA methodologies.
• Applied MLOps Practitioner
  • Hands‑on experience with model monitoring, versioning, evaluation frameworks, and production ML infrastructure.
  • Pragmatic and execution‑focused—prioritizing scalable solutions over theoretical perfection.
• Technical Proficiency
  • Strong Python skills and experience building integrations, pipelines, and tooling for ML systems.
  • Understanding of performance trade‑offs between model size, cost, latency, and accuracy.
• Cloud & Infrastructure Fluency
  • Experience working within cloud ML environments (AWS, GCP, or equivalent).
  • Ability to collaborate effectively with DevOps/SRE teams.
• Collaborative Technical Leader
  • Comfortable acting as a force multiplier for data science teams.
  • Strong communication skills and a cross‑functional mindset.

Note: Confidence gaps shouldn't hold you back. If you meet about half of the requirements and feel excited about the work, we encourage you to apply.

What You'll Receive

• People & Culture
  • Work with talented, collaborative colleagues who are passionate about their craft.
• Professional Development
  • Access to internal learning platforms, onboarding support, and ongoing training resources.
• Lifestyle Benefits
  • Meal stipends for remote work days.
  • Generous paid time off including vacations, holidays, wellness time, and parental leave.
• Health & Financial Benefits
  • Comprehensive health coverage (medical, dental, vision, life, disability).
  • Retirement savings plan options.
• Work‑From‑Home Support
  • Stipend to set up a comfortable and productive home office environment.