What are the responsibilities and job description for the Machine Learning Engineer position at Quantum Search Partners?
About the Role
Our client has built an AI-powered fashion & design prototyping platform. They are backed by investors like 500 Global and Sassafras Investments and industry leaders from the fashion and tech sectors, including the Board Member of American Eagle.
We are looking for a strong machine learning engineer to help us fine-tune and train our custom models to allow our customers to design and visualize any complex garments they envision. Along the way, we will share our knowledge on manufacturing and empower you to become a clothing expert! You will work to improve the core components of our ML stack and play a critical role in designing and deploying new ML solutions.
What You’ll Work On
Fashion design is deeply creative yet highly technical. Our users span from junior designers to creative directors and fashion design students. Building tools that meet their diverse needs is both challenging and rewarding.
Fine-tuning Diffusion (transformer) 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
Requirements
Strong proficiency in Python and its ecosystem 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
Nice to haves
Experience with frontend development frameworks (e.g., Vue.js, Angular, React)
Knowledge of database systems and data streaming technologies
Understanding of security best practices for API development and ML model serving
Experience with real-time inference systems and low-latency optimizations
Compensation :
180,000-$200,000 per year
Salary : $180,000 - $200,000
