Our client is a startup in the fashion industry and is seeking a skilled machine learning engineer to enhance their platform, which integrates a digital canvas, fabric library, and AI tools to streamline garment design. You will focus on fine-tuning and training custom models that help customers visualize complex garments. The role involves improving our ML stack, designing and deploying new solutions, and gaining expertise in clothing manufacturing.

Key Responsibilities:

Fine-tune and deploy Diffusion models for image generation and cloud inference

Convert research models into production-ready demos

Optimize model performance, scalability, and infrastructure reliability

Develop APIs for serving ML models and implement security best practices

Requirements:

Expertise in Python, machine learning, and neural networks (e.g., Diffusion models)

Strong skills in PyTorch and transformer models

Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)

Proven ability in rapid ML prototyping (e.g., Streamlit, Gradio)

Familiarity with distributed systems, model-serving, and observability practices

Nice to Haves:

Experience with frontend frameworks (Vue.js, React)

Knowledge of databases, real-time inference systems, and security best practices