Full-stack Developer

 

Description:

Job Overview: We seek a highly skilled Backend Developer with expertise in .NET and AI/ML to lead and execute critical projects. The successful candidate will be responsible for building backend software, training machine learning models, and deploying intelligent solutions for complex optimization problems. This role is an exciting opportunity for someone passionate about developing innovative technologies and working in a collaborative, dynamic environment.

 

Key Responsibilities

Web Application Development

Collaborate on the development of a robust and scalable backend for a web application using .NET framework.

AI/ML Model Development

Train an AI model using annotated images with free-form polygons to handle iterative feedback for improved annotation quality and accuracy.

Develop a learning mechanism within the AI model to refine annotation approaches over time.

Deploy and manage the model on company servers, ensuring reliable and efficient performance and availability.

Machine Learning Optimization:

Design and build ML solutions for spatial optimization, focusing on determining the optimal solution for geometric challenges.

Employ advanced ML techniques for problem-solving beyond traditional mathematical approaches.

Continuously improve model performance through data-driven iterations and evaluations.

 

Collaboration and Documentation:

Work closely with cross-functional teams to understand project requirements and deliver innovative solutions.

Document processes, workflows, and code to ensure maintainability and knowledge sharing.

 

Required Skills & Experience

Web Development:

Strong experience with .NET framework (C#, ASP.NET Core).

Proficiency in building and managing scalable, secure backend solutions.

AI/ML Expertise:

Hands-on experience with training models on annotated image datasets (free-form polygons a plus).

Experience with models such as Mask R-CNN, YOLOv5seg, DINO, and PointTend.

Familiarity with frameworks like TensorFlow, PyTorch, or similar.

Ability to develop models that iteratively improve through feedback mechanisms.

Optimization & Algorithms:

Proficiency in machine learning techniques for spatial optimization and object placement.

Understanding of mathematical optimization libraries or tools (e.g., scipy.optimize, ORTools).

DevOps & Deployment:

Experience deploying AI models on servers or cloud infrastructure (e.g., AWS, Azure).

Knowledge of containerization (Docker, Kubernetes) is a plus.

General Skills:

Strong problem-solving abilities and analytical skills.

Excellent communication and collaboration skills.

Ability to work independently and in a team setting.