AI Engineer

PatternAI, Corp.

is building a smart, privacy-first AI that helps people work faster and think clearer. We focus on

Tryn-on capabilities, AI generation capabilities, design

conversational AI ,

retrieval + knowledge systems (RAG) , and

secure, scalable AI infrastructure

designed for real-world use. Role Summary As an early-career

AI Engineer

at PatternAI, you’ll work hands-on across

generative AI (diffusion models)

and

LLM systems . You’ll prototype, ship, and improve core AI capabilities— quality, latency, reliability, and cost —in close collaboration with product and engineering.

Full-time | Remote What You’ll Do

Build and iterate on

diffusion model workflows

(e.g.,

FLUX / Stable Diffusion family ) for

training, inference, and fine-tuning Package and deploy models for production (weights, configs, versioning, reproducible runs) Build LLM features : prompting, tool use, structured outputs, and evaluation Implement and improve

RAG pipelines

(embedding, chunking, reranking, retrieval quality) Create

evaluation harnesses

(datasets, metrics, regression tests) to track quality over time Optimize inference for

speed and cost

(batching, caching, quantization basics, GPU utilization) Ship with

privacy and security

as first-class requirements Requirements (0–1 yrs)

Strong

Python

+ fundamentals in data structures/debugging Practical experience with

PyTorch

(or similar) Understanding of

diffusion basics

(VAEs, schedulers, transformer/U-Net style backbones) Familiarity with

LLMs/NLP

(tokenization, embeddings, transformers) Ability to work independently and communicate clearly in a remote team Nice to Have

Hugging Face stack: diffusers, transformers, datasets GPU/cloud experience (RunPod/AWS/GCP), Docker, Linux Prior projects in multimodal, personalization, or evaluation tooling