**** In-person interview; *** Long term project ***Linkedin Must*** Onsite - 5 days a week (Local only) ****
Job description:
Python developers to support service team
We are looking for Sr candidates 5-10 years of experience.
Team
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.
Day-to-day
- 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 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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