Python Developer

• Title: Python Developer Location: Fremont, CA must be onsite 5 days a week Duration: 6 -12 month, with extension or conversion
  Interview: In person Friday 03/27 between 10-5pm or Wednesday 04/01 between 10-5pm - please provide your availability. Duties:
• 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.
  

Top Requirements

• 3+ years of hands on experience
• Proven experience as a Python Developer with hands-on expertisein 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

Key Focus Areas

• 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