Job
Description
Design, build, and maintain scalable data pipelines and APIs using Python, TypeScript/JavaScript, and cloud platforms like Azure, AWS, or GCP, integrating with business systems via REST APIs, SOAP, or event-driven architectures. Build and optimize ML models for entity matching, text extraction (e.g., OCR, NLP), and recommendation systems using techniques like collaborative filtering, decision trees, or clustering. Collaborate with Data Engineers, Business Analysts, and senior leadership to gather requirements, build robust data architectures, and ensure data quality, integrity, and compliance. Deploy infrastructure and manage data storage using container apps, relational databases, vector stores, or data lakes, leveraging infrastructure-as-code. Implement version control and CI/CD pipelines using GitHub. Leverage data orchestration tools to manage workflows, automate model training, and apply MLOps best practices. Conduct ad-hoc analyses, derive actionable insights, and present findings to stakeholders. Stay current with advancements in AI and machine learning to drive innovation, improve existing solutions, and adapt to evolving technologies. Contribute to Scrum-based agile processes, including sprint planning and retrospectives Bachelor s Degree in computer science, Engineering, or related field 5+ years of experience in data science, AI, and software engineering. Strong programming skills in Python and JavaScript/TypeScript. Proficiency in SQL for querying and managing relational databases. Experience with cloud platforms (Azure, AWS, or GCP) and API development. Familiarity with at least one data orchestration or MLOps tool (e.g., Prefect, Data Bricks, Airflow, or Azure Machine Learning Studio). Familiarity with virtualization and IaaC tools (e.g, Docker, Bicep/Terraform). Experience with LLM APIs (e.g, OpenAI, LLama). Understanding of machine learning, NLP, and data processing techniques Comfortable in agile environments that implement Scrum
