Freelance ML/Python Developer
Summary
Freelance ML/Python developer builds and deploys computer-vision models (YOLO, DETR, ResNet) using PyTorch, optimizes inference pipelines on Nvidia GPUs, and integrates them via APIs on AWS.
Role Description
We are seeking a Freelance Sr-level Backend Developer (Machine Learning/Python). The role will tentatively start as soon as possible (June) and will continue through the end of the year. The role will be remote (but if it transitions to full-time, the role will be based in NYC).
- 5+ years of professional experience developing software in Python, with a strong focus on machine learning and applied AI.
- Hands-on experience with state-of-the-art computer vision architectures and object detection frameworks, including models such as YOLO, DETR, ResNet, and similar approaches.
- Deep expertise with PyTorch, including custom model development, transfer learning, training optimization, and deployment of production-grade machine learning systems.
- Hands-on experience developing, optimizing, and deploying real-time machine learning inference pipelines on custom Nvidia GPU hardware, with a strong understanding of performance tuning, memory management, latency reduction, and edge AI deployment constraints.
- Proven experience developing, training, and optimizing custom classification models across a variety of machine learning techniques and model architectures.
- Experience leveraging modern data annotation and labeling workflows, including open-source platforms and segmentation tools such as Meta's Segment Anything Model (SAM).
- Working knowledge of AWS cloud infrastructure and services used to support machine learning workflows and deployments.
- Experience operating within Agile development environments and collaborating across cross-functional teams.
Qualifications
- Experience developing APIs and backend services using frameworks such as Flask, Django, or similar web technologies.
- Familiarity with Ruby and Ruby-based applications.
- Experience working within Ubuntu Linux environments and deploying solutions to embedded or edge computing platforms.
- Familiarity with containerization technologies such as Docker and related deployment workflows.
Requirements
- Hourly rate dependent on years of experience, $100 up to $140/hour.
- Direct candidates only.