
• Build, deploy, and maintain production-grade AI applications and data processing pipelines.
• Apply test-driven development (TDD) principles and leverage testing frameworks to ensure robust, high-quality code.
• Collaborate closely with product managers, data scientists, engineers, and stakeholders to translate business requirements into scalable technical solutions.
• Conduct proofs of concept (POCs) to evaluate and integrate emerging technologies and methodologies.
• Work effectively within a diverse, cross-functional, and geographically distributed project team.
• Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Engineering, or a related field.
• 2+ years of hands-on experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or in a related data solutions role.
• Proven experience in deploying machine learning models, APIs, or web applications to production environments.
• Strong proficiency in Python and SQL, with Java experience considered a plus.
• Familiarity with cloud-native big data frameworks such as Hadoop, YARN, Spark, Hive, Impala, NiFi, and Airflow.
• Experience deploying solutions in cloud platforms such as AWS, Cloudera, or Databricks, and integrating data visualization tools like Tableau, Power BI, or Databricks SQL dashboards.
• Working knowledge of software engineering best practices including Git, Jira, and DevOps workflows.
• Experience in microservices architecture, data modeling, data monitoring, dashboarding, and data warehousing concepts.