Senior MLOps Engineer

Creator

IQ is the operating system for creator-led growth trusted by more than 1,300 global brands and agencies.

We’re on a mission to make businesses more human, and humans more impactful. We operate by our values — be intentional, pursue excellence every day, embrace the journey together, and be a good human — every day. Creator

IQ has earned the title of best companies to work for in multiple programs, including Built In LA and NY. It’s been named a Fastest-Growing Company in North America on the Deloitte Technology Fast 500™ for four years, was named a leader in IDC Market Scape:
Worldwide Influencer Marketing Platforms for Large Enterprises in 2025, was named a Leader by The Forrester New Wave™:
Influencer Marketing Solutions, and has been consistently recognized by G2 as a Leader, and is rated 5 stars on Influencer Marketing Hub. We operate in a flexible work model that combines both in-person and remote work to boost collaboration, enhance innovation, and adapt to individual work styles.

We’re seeking passionate, innovative minds to join our journey. Be a part of our dynamic team and let’s transform the industry together!

As a Senior MLOps Engineer on our Product Innovations team, you will serve as the technical lead for Applied MLOps, bridging the gap between experimental data science and production-grade efficiency. You will focus heavily on ground truth generation, model evaluation, and pre/post processing decisions around a scaled vector embeddings ecosystem.

• Architect Annotation & Measurement Pipelines:
  Own the design and implementation of human-in-the-loop and auto-annotation workflows. You will set up systems (e.g., Label Studio) to establish tight confidence metrics and rigorous Inter-Annotator Agreement (IAA).
• Drive Cost-Efficiency via Evaluation:
  Create the ground truth, golden sets, and by-model evaluation criteria that allows us to benchmark models and make informed data science decisions. Your work will directly impact margin by enabling us to deploy the right model for the right task.
• Enforce Applied MLOps Standards:
  Implement “model-as-a-judge” frameworks, deterministic PII scrubbing, and other best practices within our production pipelines to ensure our model-driven products are robust and compliant.
• Collaborate on Model Strategy:
  Work closely with our Data Science team to make applied generative decisions that result in stronger product outcomes and cost efficiencies.
• Build & Integrate:
  Collaborate with engineering to integrate measurement loops into our broader infrastructure (AWS/GCP), ensuring our model lifecycle is automated and observable.

• Annotation & Evaluation Expert:
  You have deep experience setting up annotation work streams (using tools like Label Studio, Scale AI, or custom solutions) and know how to calculate and improve ground truth quality.
• Applied MLOps Practitioner:
  You care about execution over policy making. You have experience implementing model monitoring, versioning, and evaluation loops in a production environment.
• Python Proficiency:
  You possess strong proficiency in Python, capable of writing the glue code, scripts, and API integrations necessary to bind our models to our application stack.
• Model Optimization Mindset:
  You understand the trade-offs between model performance, latency, and cost. You are excited about the challenge of proving that a smaller model can do the job of a massive LLM.
• Cloud & Infrastructure Fluency:
  You are comfortable working within AWS (Sagemaker, S3) and GCP (Vertex AI) environments and can interface effectively with Dev Ops to deploy your solutions.
• Collaborative Leader:
  You can act as a force multiplier for our Data Science team, equipping them with the tools and data they need to move faster.

Confidence can sometimes hold us back from applying for a job. But we’ll let you in on a secret: there’s no such thing as a ‘perfect’ candidate. Have 50% of the criteria? Excited about this opportunity? Passionate about what we do at Creator

IQ? Please apply! Creator

IQ is a place where everyone can grow.