Machine Learning Engineer Opportunity
About the Company
Our client is an innovative startup revolutionizing the fashion industry through cutting-edge technology. They are transforming how designers and supply chain teams collaborate, combining the creativity of a digital canvas with AI-powered tools to streamline workflows, reduce costs, and bring collections to market faster.
Since launching in 2023, the company has made significant strides:
- Increased productivity for design teams by over 40 hours per week.
- Achieved 12x ARR growth in just one year.
- Partnered with 7 of the top 10 U.S. fashion design schools, including Parsons, SCAD, and FIT.
This is an opportunity to join a high-growth startup reshaping a global industry.
Role Overview
As a Machine Learning Engineer, you will play a critical role in fine-tuning and training custom models to help customers design and visualize complex garments. You'll improve the core components of the machine learning stack and design and deploy new ML solutions. This is an exciting opportunity to apply cutting-edge AI technologies in a creative, high-impact environment.
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.
- Designing, deploying, and maintaining Diffusion models for cloud-based inference.
- Transforming research models into production-ready demos and MVPs.
- Optimizing model inference for improved performance and scalability.
- Ensuring high availability and reliability of model serving infrastructure.
- Ensuring security best practices across the ML infrastructure.
- Developing and maintaining robust APIs for serving machine learning models.
What We're Looking For
- Strong proficiency in Python and its ecosystem for machine learning, transformer models, data analysis, and other neural network architectures.
- Experience fine-tuning Diffusion models for image generation, image upscaling, and in/out painting models.
- Deep understanding of effectively evaluating image generative models.
- Strong proficiency in PyTorch and 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
- Base Salary: $180k–$200k/year.
- Equity: Meaningful early-stage equity with high growth potential.
- Benefits: Comprehensive health, dental, and vision insurance.
Location
This is a hybrid role based in New York City. Candidates must be located in NYC and available for in-person collaboration as needed.