Kodex

Machine Learning Engineer

• Build and deploy models to detect and flag suspicious behavior (classification, anomaly detection, clustering, ranking, and other approaches as appropriate)
• Own ML pipelines end-to-end (feature generation, training, evaluation, batch/streaming inference, backfills, and versioning)
• Design evaluation + monitoring: ground truth strategies with Threat Intel, offline metrics, drift monitoring, and alerting
• Collaborate with product & engineering to integrate intelligence into user-facing workflows (e.g., review queues, and decision-support tooling)
• Improve data quality and accessibility by working with data engineering patterns (schemas, lineage, reproducibility, and access controls)
• Contribute to operational rigor: runbooks, incident response, and safe rollout practices for systems that impact customer trust

ML Engineer – Verifications

Full-stack Engineer

• Build and operate customer-facing integrations (APIs, identity federation, webhooks, imports/exports, and marketplace apps) that reduce manual work for customers, unblock new product workflows, and raise the reliability and security bar across the platform.
• Work closely with Product, Customer Success, and fellow engineers to design, develop, and ship integration capabilities that unlock new workflows.
• Building external-facing APIs and “Bridge” infrastructure for ingest/egress of requests between Kodex and third-party systems.
• Shipping identity and verification integrations such as “Sign in with Kodex (OIDC)” and related security reviews, test environments, and customer enablement.
• Delivering cross-border / government portal integrations that require careful spec compliance, auditing, and operational rigor.
• Productizing existing bespoke integrations into reusable, scalable primitives.
• Building self-serve integrations that eliminate manual setup and reduce on-call/customer support load.
• Improving reliability and observability across integration surfaces.
• Participate in on-call rotations to maintain system reliability and respond to incidents.
• Raise the bar on engineering quality through thoughtful architecture, testing, and pragmatic refactors.

ML Engineer – Verifications

Software Engineer – Integrations