AI Platform Engineer (MLOps & Inference)

PixaSocial Ai builds viral social content on proprietary psychology and psychographic models, published across Instagram, X, LinkedIn and 12+ channels.

THE ROLE
Build the platform that makes our generation stack fast and cheap: GPU utilisation, batching, latency reduction, cost per asset - the infrastructure behind image, video and voice generation.

WHAT YOU WILL DO
- Own inference infrastructure: GPU scheduling and optimisation, batching, caching, model routing, autoscaling.
- Drive down cost per generated asset and p95 latency, with numbers to show for it.
- Build the deployment and observability path for new models: rollout, canary, rollback, health and drift signals.
- Make capacity legible: queue depth, saturation, spend, per-workspace usage.
- Work with backend and psych-stack engineers on job orchestration from request to stored asset.

WHAT WE ARE LOOKING FOR
Mid-level platform/MLOps engineer who has run GPU workloads in production and can talk in dollars and milliseconds. Python plus infrastructure tooling; containers and IaC. US-based, remote or hybrid.

NICE TO HAVE
Diffusion/LLM serving at scale, spot/preemptible capacity, multi-region cost control.

HOW TO APPLY (REQUIRED FOR THE NEXT INTERVIEW ROUND)
We only advance people who have used the product.
1. Create a free account at app.pixasocial.com/register
2. Use PixaSocial yourself: build an audience or campaign, generate content, try publishing/scheduling, and notice what is strong and what is broken.
3. Email with your resume and a cover letter that is not a CV rewrite - explain specifically how you would improve PixaSocial in this role: what you used, what you would change first, and why you are the person to do it.

Applications without a product-based cover letter will not be selected for interview.

Pixasocial LLC, 1209 Mountain Road PL NE Ste N, Albuquerque, NM 87110, USA. Equal-opportunity employer.