Cradlepoint is looking for a self-directed and skilled Data Science with Python Developer to support software developers, database architects, data analysts, and AI / ML architects on various internal and external data science and AI / ML related initiatives and projects that run in cloud-based environments. You'll be comfortable supporting the data analytics and AI / ML needs of multiple teams, systems, and products, and will be responsible for integrating created solutions with the architecture used across the company and its customers.
What You Will Do : Key Responsibilities
- Design, Architect, and Deliver AI / ML and / or Generative AI solutions hand-in-hand with business representatives, always considering the business ROI.
- Create and maintain optimal data pipeline architecture for efficient data flow and processing.
- Identify Data intensive and AI / ML Use Cases for different existing Managed Service accounts.
- Prepare technical presentations, design documents, and demonstrations for customer presentations on Data strategy and AI / ML Solutions.
- Prepare design and solution documents for both classic AI / ML and Generative AI-based solutions.
- Assemble large, complex data sets that meet various functional and non-functional business requirements.
- Design solutions that will keep data separated and secure across national boundaries through multiple data centers and strategic customers / partners, adhering to international security standards, organization, and customer security requirements.
What You Will Bring : Required Qualifications
Experience : 9 - 17 years of Telecom / IT experience in a Data-related Role with AI / ML and Data Science experience.Python Development : At least 5 years of experience using Python for AI / ML and automation , with proficiency in commonly used data engineering and machine learning libraries (e.g., pandas, numpy, scikit-learn ).Data Pipeline Development : Experience with data pipeline development in technologies like Elastic (ELK) Stack, Hadoop, Spark, Kafka , etc.Database Knowledge : Experience with Relational SQL and NoSQL databases , such as Postgres and Cassandra.MLOps Experience : Hands-on experience with MLOps , including Model deployment and monitoring .AI / ML Solutions : Proven experience in developing AI / ML Solutions for prediction, classification, and Natural Language Processing .Generative AI Technologies : Working knowledge of Generative AI technologies like Large Language Models (LLMs), Agentic AI architecture, RAG (Retrieval-Augmented Generation), and other developing technologies.Containerization : Hands-on experience with Kubernetes and containerization technologies (e.g., Docker) .Operating Systems & Scripting : Proficiency in Linux & Shell scripting knowledge.Skills Required
Python Development, Automation, AI ML, Data Pipeline, MLops, containerization , Operating System