Python Developer

Diverse team with a mix of Senior, Mid-level, and Junior Developers working in a POD model structure. The QA team operates independently. The environment is fully Agile with biweekly sprints and releases, and it moves at an extremely fast pace.

Design, develop, and maintain AI-driven applications and services using Python and modern machine learning frameworks

Write clean, efficient, and scalable code with a strong focus on algorithms, data structures, and performance optimization

Build and optimize data pipelines for training, validating, and deploying machine learning models at scale

Collaborate with data scientists, ML engineers, and product teams to translate business requirements into robust AI solutions

Implement best practices in software engineering, testing, and version control to ensure high-quality deliverables

Optimize AI/ML workloads for speed and scalability across distributed computing environments

Stay current with advancements in AI, ML, and deep learning technologies, bringing innovative solutions into production systems

3+ years of hands-on experience

Proven experience as a Python Developer with hands-on expertise in building production-grade applications

Must be hands-on with coding and demonstrate strong programming foundations (data structures, algorithms, object-oriented design)

Strong background in AI/ML with experience using frameworks such as TensorFlow, PyTorch, or Scikit-learn

Proficiency in data handling and manipulation using libraries like NumPy and Pandas

Experience with SQL databases for managing and accessing training data

Knowledge of model deployment and scaling in enterprise or cloud environments (AWS, Azure, or Google Cloud Platform)

Familiarity with containerization and orchestration (Docker, Kubernetes) for AI/ML workloads (preferred)

Strong debugging, optimization, and performance-tuning skills for both code and AI models

Python Development: Core programming language for AI/ML applications

AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn

Data Pipelines: ETL, preprocessing, and feature engineering for large datasets

SQL Databases: Schema design, query optimization, and handling structured data

Enterprise-Scale AI: Building secure, reliable, and scalable AI solutions

Hands-On Programming: Strong coding discipline with emphasis on maintainability and performance

Cloud & Deployment (Preferred): AWS/Google Cloud Platform/Azure, Docker, Kubernetes