Job Title: Python Developer
Duration: 12 months, with extension / conversion
Location: Fremont, CA must be onsite 5 days a week
Interview Process: 2 rounds of interview:
1st round 45 minutes video call (10 minutes intro, rest hands on coding)
2nd round: face to face at client's office in Fremont, CA
Team Overview
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.
Duties/Day to Day Overview
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- Must haves
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
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
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