Hire Python Developers | Vetted Senior Talent

Tech stack: Python, Flask, JavaScript, React, Redux, React Native, Angular, Next.js, Node.js, MongoDB, MySQL, PostgreSQL, Docker, AWS

A skilled full-stack developer with 4 years of experience in Python and JavaScript technologies. Builds full-stack web applications with Flask, React, Redux, Next.js, and Angular, plus mobile solutions with React Native. Has extensive expertise in developing REST APIs for front-end consumption. Has experience implementing responsive UI components and managing state in single-page applications.

Tech stack: Python, Django, PostgreSQL, Redis, Celery, Docker, AWS, Git, Jenkins, SQLAlchemy, pytest, SQLite, MySQL, FastAPI

A Python backend developer with 7 years building server-side systems for SaaS platforms. Designs RESTful APIs and manages relational database schemas using Django ORM and raw SQL. Implements caching strategies with Redis and handles background job processing through Celery workers. Sets up CI/CD pipelines with Jenkins and deploys containerized applications on AWS infrastructure. Has experience optimizing query performance and refactoring legacy codebases.

Tech stack: Python, FastAPI, Django, PostgreSQL, Redis, AWS, Docker, Kubernetes, Jenkins, GitLab CI, Bash, Git

A Python backend engineer with 4 years of experience building server-side services for cloud-native products. Designs FastAPI and Django backends backed by PostgreSQL and Redis, and writes serverless functions with AWS Lambda for event-driven backend workflows. Comfortable with Docker container orchestration on Kubernetes and CI/CD pipelines in Jenkins and GitLab CI. Has a platform engineering background that supports backend deployment when teams need it.

Tech stack: Python, TensorFlow, PyTorch, OpenCV, scikit-learn, Pandas, NumPy, LangChain, XGBoost, spaCy, AWS, Docker

A Python machine learning engineer with 7 years of experience. Builds and deploys machine learning models for predictive analytics and recommendation systems. Handles feature engineering with Pandas and NumPy, then trains algorithms with TensorFlow and PyTorch. Has been working with LLMs and generative AI for the last few years, covering prompt engineering, vector databases, RAG systems, and LLM evaluation pipelines. Also has a background in commercial computer vision and image processing projects.

Tech stack: Python, Django, Flask, JavaScript, TypeScript, React, Vue, PostgreSQL, Docker, Docker Compose, AWS, Redux, Redis, MongoDB, MySQL, ElasticSearch, SQLAlchemy

A Python programmer with a focus on full-stack web development with Django and React/Vue. Writes RESTful APIs for front-end applications and ensures efficient database interactions using Django ORM and optimized SQL queries. Implements state management in client-side apps with Redux. Has used Vue and TypeScript to build interactive analytics dashboards for clients.

Tech stack: Python, Django, FastAPI, PostgreSQL, MySQL, RabbitMQ, Docker, pytest, NumPy, Pandas, Jupyter Notebook, SciPy, TensorFlow, Matplotlib

A senior Python backend engineer with 5 years of experience building server-side systems for financial services products. Develops Django and FastAPI backends that expose trading analytics, risk assessment models, reporting APIs, and portfolio dashboards to web clients. Designs PostgreSQL schemas for time-series financial data and uses RabbitMQ for asynchronous job processing across reporting pipelines. Recently delivered a Python-based pricing engine for an options trading platform that processes live market data feeds end of day.

Tech stack: Python, Apache Spark, PySpark, Apache Airflow, SQL, PostgreSQL, MongoDB, Pandas, MySQL, Oracle, MariaDB

A data engineer with 6 years of commercial experience. Develops scalable ETL pipelines for data warehousing and analytics systems. Uses Apache Spark for distributed data processing and Apache Airflow to orchestrate complex data workflows. Writes SQL transformations for data cleansing and validation. Works with both relational databases (e.g., PostgreSQL, MariaDB, MySQL, Oracle) and NoSQL solutions like MongoDB for varied storage needs.