Muhammad Atif

Python Developer

Coder Crew • Teilzeit

Feb 2025 - Present • 1 yr 3 mos

Backend API Development: Developed and maintained RESTful APIs for a SaaS real estate platform using Django and FastAPI, including secure authentication and user management with JWT (Python-JOSE). AI Model Training & Deployment: Trained and deployed a YOLOv8 computer vision model for image detection tasks. Utilized Roboflow for dataset annotation and management, and leveraged Grounding DINO and SAM (Segment Anything Model) to develop and experiment with automated labeling and segmentation workflows for enhanced data efficiency. Database Management: Managed PostgreSQL databases using Alembic migrations and SQLAlchemy ORM; wrote optimized raw SQL queries for better performance. Vector Databases: Integrated vector databases (Weaviate, Pinecone, Chroma) to support AI features like semantic search and recommendation. Collaboration & Agile: Participated in Agile sprints, daily stand-ups, and code reviews; contributed to technical documentation ensuring maintainable and scalable backend solutions. Web Scraping & Automation: Developed automated data extraction pipelines using BeautifulSoup and Playwright, enabling efficient web scraping, structured data collection, and preprocessing for AI and analytics workflows.

Software Engineer AI/ML

Maverick • Vollzeit

Jul 2024 - Jul 2025 • 1 yr

AI Agent & Chatbot Development: Developed advanced AI agents using LangChain, LangSmith, and LLM orchestration. Built voice/chat agents tailored to user behavior and context. Deployed AI agents as production-ready Flask/FastAPI APIs for smooth frontend integration. Machine Learning & Deep Learning: Built and trained ML/DL models using TensorFlow, PyTorch, and Scikit-learn. Performed data preprocessing with Pandas/NumPy and optimized pipelines for accuracy and performance. LLM & RAG Solutions: Implemented Retrieval-Augmented Generation systems using Pinecone, Weaviate, and Chroma. Added embeddings, custom retrievers, and document loaders for high-accuracy AI answers. Backend Development: Built secure, scalable REST APIs with FastAPI, Flask, and Django. Implemented JWT auth (Python-JOSE), Pydantic validation, and modular architectures. Database & Migrations: Managed PostgreSQL using SQLAlchemy and Alembic. Wrote optimized SQL queries and integrated vector databases for AI search and retrieval. Client Communication & Project Closing: Joined client meetings to explain AI architectures, propose solutions, and answer technical questions helping win and close multiple projects. Documentation & Reporting: Created clean documentation, API references, and ML model performance reports for teams and clients. Problem-Solving & Coding Challenges: Solved data-structure and algorithm problems to write clean, optimized Python solutions. Continuous Learning & Certifications: Completed training in ML, Reinforcement Learning (AWS DeepRacer), and Generative AI with AWS to stay updated with modern AI advancements.

AI/ML Engineer

NETSOL Technologies • Vollzeit

Jul 2019 - May 2024 • 4 yrs 10 mos

AI Agent & Chatbot Development: Designed and deployed an AI-driven conversational agent for the ScentWork platform, using LangChain and LangSmith to dynamically adjust chat flows based on user type, context, and journey. Packaged and deployed AI agents as Flask-based APIs, enabling seamless frontend integration. Machine Learning Models: Assisted in developing and training ML models (TensorFlow, Scikit-learn); performed data preprocessing with Pandas and NumPy. Closer Role: Actively participated in client calls and helped close projects by presenting technical solutions, explaining AI system design, and answering technical questions, directly contributing to winning new projects. Backend APIs: Built RESTful APIs using FastAPI, Flask and also with Django; implemented data validation (Pydantic) and secure JWT authentication (Python-JOSE) in case of Flask and FastAPI. Database Management: Managed PostgreSQL with Alembic migrations and SQLAlchemy; wrote optimized raw SQL queries; integrated Vector Databases (Weaviate, Pinecone, Chroma) to support AI retrieval and embeddings use cases. Documentation & Reporting: Documented project steps and findings, creating simple reports on model performance and key metrics to share with team members. Solving Python coding assessments: Tackled various algorithmic and data structure challenges, focusing on optimizing solutions for efficiency and readability. Developed a strong understanding of problem-solving techniques and enhanced Python proficiency. Continuous Learning: Completed internal courses in Machine Learning, Reinforcement Learning (AWS DeepRacer), and Generative AI with AWS.