Streaming ML Engineer
Role summary
We are seeking a Streaming ML Engineer to design, develop, and maintain AI-driven applications and services. This role requires strong Python programming skills, hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn, and proficiency in building and optimizing data pipelines. You will collaborate with cross-functional teams to translate business needs into scalable AI solutions, focusing on performance optimization and best practices in software engineering. Experience with SQL databases and cloud environments (AWS, Azure, GCP) is essential. Familiarity with Docker and Kubernetes is preferred. The ideal candidate has 3+ years of experience and a solid foundation in data structures, algorithms, and object-oriented design.
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 practi ces 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
For applications and inquiries, contact: hirings@openkyber.com