Python and AI/ML Lead developer

Position Overview

• Python (3.8+) with advanced expertise, including FastAPI framework for scalable web

applications.

• FastAPI Framework for designing and developing robust APIs.
• PostgreSQL/MongoDB for advanced database design, optimization, indexing, and

performance tuning.

• Docker for containerization and orchestration in development and production

environments.

• Redis for efficient caching, session management, and real-time data processing.
• Celery for background job processing, task queues, and asynchronous execution.
• Should be familiar with ETL
• Strong experience with PyTorch or TensorFlow.
• Expertise in computer vision (pose estimation, segmentation, GANs).
• Familiarity with virtual try-on frameworks like VITON.
• Knowledge of video processing (OpenCV, FFmpeg).
• Experience with REST API integration and model serving (TorchServe, FastAPI).
• Background in AI model optimization for real-time or near-real-time applications.
• Familiarity with Elasticsearch and vector similarity search.
• Understanding of asynchronous programming and real-time systems.

Security Expertise

• Strong knowledge of security vulnerability assessment and remediation techniques.
• Experience in implementing Authentication & Authorization systems (JWT, OAuth

2.0).

• Proficiency in data encryption, secure storage, and data handling practices.
• Implementation of security headers, CSRF protection, and input validation to

prevent common vulnerabilities.

• Expertise in secure coding standards and compliance best practices.

Key Responsibilities

• Lead the design, architecture, and development of AI/ML-driven applications and

solutions.

• Collaborate with product managers, data scientists, and business stakeholders to define

technical requirements and translate them into robust solutions.

• Build, train, and optimize ML/DL models for applications such as NLP, Computer Vision,

Recommendation Systems, and Predictive Analytics.

• Mentor and guide junior developers and data engineers in coding best practices, model

implementation, and system design.

• Ensure scalability, performance, and deployment of ML models into production

environments (cloud/on-premises).

• Evaluate new tools, frameworks, and technologies to improve AI/ML capabilities and

development processes.

• Oversee code reviews, model validation, and MLOps pipelines for CI/CD integration.
• Collaborate with the DevOps and Data Engineering teams for seamless data pipeline

and model deployment.

• Stay updated with the latest advancements in AI/ML research, Python frameworks, and

industry practices.

• Develop, train, and fine-tune deep learning models for StyleDNA vector generation and

virtual try-on systems.

• Implement pose estimation, segmentation, and garment warping algorithms.
• Collaborate with backend engineers to deploy ML models via APIs.
• Continuously improve model accuracy through incremental learning from user

interactions.

• Work with large-scale video data processing pipelines.
• Design and develop RESTful APIs for user management, StyleDNA vector storage, and

recommendations.

• Implement data pipelines for processing user interactions and triggering model updates.
• Integrate AI/ML model inference with backend services.
• Ensure data consistency, security, and efficient handling of large volumes of interaction

data.

• Build real-time notification systems using WebSockets or push notifications.

  Role & responsibilities

Preferred candidate profile