Machine Learning Engineer - Hamlyn Williams : Job Details

I am partnered with an exciting Fashion Tech startup who recently closed a seed round of funding and already has an established client base. They are looking to expand their team with a Machine Learning Engineer, who is able to work Hybrid out of their NYC Office.

Responsibilities:

● Fine-tuning Diffusion models for image generation

● Design, deploy, and maintain Diffusion models for cloud-based inference

● Transform research models into production-ready demos and MVPs

● Optimize model inference for improved performance and scalability

● Ensure high availability and reliability of model serving infrastructure

● Ensure security best practices across the ML infrastructure

● Develop and maintain robust APIs for serving machine learning models

Qualifications:

● Strong proficiency in Python for machine learning, transformer models, data analysis, and other NN architectures.

● Fine-tuning Diffusion models for image generation, image upscaling, in and out painting models, etc.

● Deep understanding of how to effectively evaluate image generative models

● Strong proficiency in PyTorch, transformer models

● Knowledge of cloud platforms (AWS, GCP, or Azure) for deploying and scaling ML services

● Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes)

● Proven track record in rapid ML model prototyping using tools like Streamlit or Gradio

● Experience with distributed task queues and scalable model serving architectures

● Understanding of monitoring, logging, and observability best practices for ML systems.

• It is strongly preferred that candidates come from a SaaS start up or a small start up environment.

This role cannot offer any VISA Sponsorship. Candidates must be a US Citizen or Greencard Holder