Jobs at adjoe

Build and operate high-performance backend services and real-time analytics for advertising dashboards. Design microservices, ingest and process massive event streams (Kafka/Kinesis), optimize Go services for high throughput, and ensure low-latency queries against Druid and MySQL. Deliver well-documented APIs for partner-facing dashboards and collaborate with frontend teams using TypeScript/React. Contribute to end-to-end service ownership and infrastructure improvements.

Manage day-to-day operations of the Singapore office: own space planning, vendor/contracts, inventories and budgets; liaise with building management and global IT; design and run employee events and onboarding; support local Talent Acquisition and HR to deliver a high-engagement workplace.

Build and maintain high-throughput Go microservices handling 2M+ daily interactions. Design event-driven pipelines (Kafka/SQS/SNS/Kinesis), optimize APIs and queries across DynamoDB, MySQL, Druid, and Athena, integrate ML algorithms with the Data Science team, implement secure callbacks (OAuth2, mTLS, HMAC), and collaborate across international teams. Use Terraform, Docker, and serverless tooling to deploy reliable, scalable systems.

Lead and execute global creative direction for adjoe, managing a 4-5 person design team across time zones. Ensure brand consistency across channels, translate commercial objectives into high-converting design, develop scalable templates and brand guidelines, and deliver assets for web, events, presentations, data visualization, and performance marketing. Act as player-coach and collaborate closely with Growth, Product Marketing, and Content.

Own demand and supply partnerships in Korea: source and close mobile gaming advertisers and app publishers, manage pipeline, conduct market research, onboard clients, prepare sales presentations, and coordinate with internal teams to grow revenue and optimize partner monetization.

Design, build, and productionize large-scale recommendation and bidding ML models. Own the full ML lifecycle from feature discovery and training to deployment, real-time low-latency inference, monitoring, and A/B experimentation. Collaborate with backend and data engineering teams to integrate models and iterate on performance.

Lead the Dashboards team as a senior Go engineer and architect: design and operate adtech-scale distributed systems, build real-time analytics pipelines and dashboards (50M+ daily events), own partner-facing APIs and microservice integrations, optimize columnar DB queries (Druid/ClickHouse), work with TypeScript/React frontends, and manage and develop engineering team members while aligning technical decisions with business needs.

Lead technical analyses to detect and prevent ad fraud at scale. Build and optimize SQL/Python data pipelines, apply anomaly detection methods, design experiments, automate reusable analytics frameworks, and communicate findings to technical and non-technical stakeholders to drive business decisions.

Create and maintain developer-facing documentation (API references, SDK guides, integration tutorials, sample apps). Build demo apps in Swift/Kotlin, contribute to Docusaurus/Markdown tooling, use JavaScript/TypeScript/HTML for components, debug integrations using SQL, logs, and dashboards, and collaborate cross-functionally to improve developer experience and reduce integration friction.

Build and maintain ML-scale data infrastructure: feature store, real-time and batch pipelines, data quality and validation, and low-latency systems. Translate Data Science needs into high-performance Flink streams, eliminate ETL bottlenecks, collaborate on online ML systems, and implement monitoring, governance, and deployment processes for production ML workflows.

Lead and grow the Data Science team owning the real-time bidding algorithm, combine hands-on modeling with people leadership, architect and deploy large-scale ML systems, run experiments and A/B tests, and align model work with product and infrastructure priorities to drive ad monetization and business outcomes.

Own the Analytics Dashboard product end-to-end: define roadmap, manage a dedicated development team, run agile delivery, prioritize by user and business KPIs, bridge business and engineering, deliver 0-to-1 iterations, and grow team members while optimizing campaign management and real-time analytics.

Own reporting, data analysis and KPI evaluation for business teams; gather and document business needs; model processes; identify risks and opportunities; outline business impact; communicate insights and implement/test solutions.

Drive publisher acquisition and revenue in Japan by managing pipeline, lead generation, outreach, closing, onboarding, and growth. Use CRM and Google Suite to prepare custom presentations, attend events, and relay partner needs to internal teams to win enterprise clients.

Lead global GTM strategy and execution across Europe, North America and APAC. Support strategic sales accounts, build sales enablement, reporting and pipeline frameworks, design global sales incentives, and establish the Revenue Operations function to scale commercial operations and ensure cross-functional alignment with Product and Tech.

Identify and evaluate potential advertisers for adjoe's UA solution; onboard and maintain advertiser relationships; monitor sales pipeline and partner KPIs; develop pitches and presentations; attend conferences and meet partners; collaborate cross-functionally to achieve company goals.

Lead strategic and technical product initiatives across adjoe’s high-scale adtech platform. Define vision, translate business goals into technical roadmaps, coordinate cross-functional teams, make executive trade-offs, measure outcomes with KPIs, and mentor team members. Ensure product decisions align with system design, scalability, and revenue impact while collaborating with Data Science, Data Engineering, and Analytics.

Design, operate, and optimize cloud infrastructure at scale for high-throughput ad systems. Manage Kubernetes clusters, Kafka streaming, Terraform IaC, CI/CD pipelines, AWS services, and open-source data infrastructure. Drive cost-efficient, reliable platform operations and migrate workloads to self-hosted solutions while supporting backend teams and improving observability and automation.

Lead production-scale MLOps: deploy and maintain low-latency ML models, build continuous training pipelines, implement observability for data drift, optimize inference (Triton/ONNX/TF Serving), own ML platform integration with Kubernetes/Docker and orchestration tools, and collaborate with infra and data science teams to keep models performant at massive scale.

Build and maintain data-rich dashboards and campaign management tooling using React and TypeScript. Implement data fetching with RTK Query and SQL, create visualizations, ensure test coverage with Jest and Cypress, use CI/CD with Docker and GitLab, promote reusable code via npm/yarn workspaces, and mentor junior developers while improving frontend architecture and maintainability.