• Contribute to the foundational technology powering Adaptive ML, with support and guidance from the team • Help advance projects by implementing features, running experiments, or improving reliability • Communicate clearly about your work and learn to collaborate in a distributed team environment • Write clear, well-structured code (primarily in Python; exposure to systems programming is a plus, not a requirement) • Help debug issues in distributed or ML-heavy systems • Learn best practices for performance, testing, and robustness • Assist with research on large language models and reinforcement learning • Reproduce and analyze results from recent ML literature • Support empirical experiments and help document findings • Interns are encouraged to explore both areas of engineering and research

• Remote position • Projects involving Zoho products • Development of integrations • Collaboration with global teams.

• Design and implement integrations between Oracle HCM Cloud and external systems. • Query and optimize Oracle HCM tables and metadata; ensure referential integrity across HR, benefits, and time data. • Develop high-quality code using PL/SQL, SQL, and scripting languages for transformations, validations, and automation. • Build interfaces using HCM Extracts, HDL, Fast Formulas, BI Publisher, and OIC or similar middleware. • Implement REST/SOAP APIs, SFTP/file-based transfers, and secure integration patterns. • Optimize queries and batch processes for large-scale HCM data operations. • Enforce data privacy (PII), SOX controls, and audit readiness. • Instrument integrations with logging and alerts; troubleshoot and resolve issues promptly. • Create technical specs, mappings, and runbooks; maintain version control and CI/CD pipelines. • Work closely with HRIS, Payroll, and IT teams; mentor junior developers.

• Design, implement, and operate high volume services in Go on top of Kubernetes/GCP/AWS • Build operational tooling for the code you write, and work with cloud infrastructure engineers to manage your code in production • Contribute to the direction of the product, and help evolve the overall platform architecture to meet product and scale needs • Refine the way we build and release the platform by contributing to build systems, test frameworks, deployment tools and monitoring