• Fullstack Development: Build and evolve features on both the backend (APIs, integrations, business logic) and frontend (dashboards, operational flows, and user interfaces). • Core Module Development: Work directly on core modules such as Campaign Engine, Customer Profile, Integration Hub, and Channel Orchestrator. • Integrations: Develop and maintain integrations with external APIs (ERPs, WhatsApp, VOIP, payments, etc.), ensuring stability and scalability. • API Design: Create well-defined APIs (REST/gRPC) with a focus on decoupling and inter-service communication. • Data Modeling: Participate in defining and evolving data structures, ensuring consistency and performance. • Functional Frontend: Build simple, efficient interfaces (manager dashboards, onboarding, operational flows), prioritizing usability and fast delivery. • Observability and Debugging: Monitor logs, metrics, and system behavior to quickly identify and resolve issues. • Code Quality: Write clean, testable, and scalable code, following good versioning and review practices. • Collaboration: Work closely with backend, AI, product, and operations teams to ensure deliveries are aligned with business objectives.

Role Description Build feature stores for online inference and model training, tools that enable machine learning engineers (MLEs) and data scientists (DSs) to improve the ML feature software development lifecycle. - Lead the building, testing, and maintenance of our ML Feature Store and Feature Engineering infrastructure at Reddit that serves 100 million+ redditors. - Work with other engineers across ML Platform and Reddit infrastructure to significantly advance the ML Platform. - Work with management on team goal setting, planning, and de-risk project execution. - Mentor other team members in adopting a rigorous DevOps approach to maintain and/or improve ML infra components and services health and quality. Full-time telecommuting is an option. Qualifications - Master’s degree (or its foreign equivalent) in Computer Science, Engineering (any field), Data Science, or closely related quantitative discipline. - Two (2) years of experience in the job offered or in any occupation in a related field. Requirements - Designing and building machine learning model serving infrastructure. - Deploy models for serving in production. - Enhancing machine learning (ML) observability of feature drift detection and model performance. - Python. - Git. - SQL or MYSQL. - Designing technology stacks. - Debugging and monitoring for production services. - Any suitable combination of education, training, and experience is acceptable. Benefits - Comprehensive Healthcare Benefits and Income Replacement Programs. - 401k with Employer Match. - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support. - Family Planning Support. - Gender-Affirming Care. - Mental Health & Coaching Benefits. - Flexible Vacation & Paid Volunteer Time Off. - Generous Paid Parental Leave.

• Teach the following courses and learning modules: Linux Essentials, LPIC-1 Linux Administrator (including exam preparation) • Learning module "Provisioning networks and services" • Learning module "Deploying service daemons and automating administrative tasks" • Learning module "Ensuring operation and security of networked systems"

• Build a film crew marketplace connecting production teams with talent globally. • Implement 'Go to set' features enabling real-time crew coordination and logistics. • Develop AI-powered features leveraging multiple generative models (OpenAI, Fal.ai, Nano Banana 2, Seedance). • Create full-stack features with React frontend, Node.js backend, and MongoDB. • Deliver MVP-state features shipped in hours, not weeks — fast iteration, high autonomy.