2026 Freelance ML/Python Developer

Smart Design•,

1d•$100 - $140•Remote

About The Position

We have an opportunity to join an exciting startup in the smart consumer appliance space! 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).

Requirements

5+ years of professional experience developing software in Python
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.

Nice To Haves

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.

Responsibilities

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.