Jobs at adjoe

Manage and grow a portfolio of app publisher partners in Japan, build strong partner relationships, analyze CPI/CPM/CTR/ARPDAU to optimize monetization, present performance reports and QBRs, collaborate cross-functionally to solve issues, identify upsell opportunities, and drive revenue and retention targets.

Conduct advanced machine learning research and translate state-of-the-art generative AI, recommendation, embedding, and ranking methods into high-throughput production systems. Build multi-stage recommendation pipelines, optimize large models for sub-millisecond latency, and develop user and ad embeddings using PyTorch and GPU infrastructure. Lead architectural discussions, mentor junior scientists, and guide research direction across systems serving hundreds of millions of users.

Develop and productionize reinforcement learning, optimization, and control-theory algorithms for real-time bidding, auctions, budget pacing, and allocation. Translate research into sub-millisecond, high-throughput systems using large-scale Bayesian inference and behavioral data. Lead technical architecture, define mathematical objectives with product and engineering teams, mentor junior scientists, and guide research direction across adtech products serving hundreds of millions of users.

Build and operate high-throughput Go microservices powering real-time ad targeting and billions of advertising events. Design Kafka, SQS/SNS, and Kinesis event pipelines; optimize DynamoDB, MySQL, Druid, and Athena queries; develop open APIs; integrate machine learning algorithms; and collaborate with data science and backend engineering teams.

Manage and grow a portfolio of app publisher partners in the adtech ecosystem. Identify upselling and monetization opportunities, analyze CPI, CPM, CPC, ARPDAU, and CTR metrics, and implement performance improvements. Build partner relationships, deliver data-driven reports and QBRs, translate feedback into technical requirements, and collaborate with Product, Tech, and Business teams to resolve integration blockers and drive portfolio growth.

Build and operate high-performance Go backend services, distributed microservice systems, analytics engines, campaign APIs, and partner-facing data products. Process billions of events through Kafka and Kinesis, optimize Druid and MySQL queries for real-time insights, and support React and TypeScript dashboards. The role involves profiling Go applications, designing scalable APIs, and owning services in a Kubernetes-based environment.

Develop and maintain full-stack web and server applications supporting adjoe’s global adtech platform. Build reliable Golang microservices, performant TypeScript and React frontends, and integrations using REST, GraphQL, WebSockets, and HTTP. Improve architecture, APIs, diagnostics, and platform stability across distributed systems. Participate in code reviews, mentor junior developers, collaborate internationally, and contribute to scalable solutions for enterprise publishers and partners.

Supports Demand Partnerships Managers with advertiser and publisher onboarding, campaign setup, tracking verification, KPI monitoring, and early campaign scaling. Maintains Salesforce pipeline data, assists with sales presentations and market intelligence, and collaborates with Account Management, Technology, and Product teams to resolve launch issues. The role offers a pathway to a closing Demand Partnerships Manager position.

Manage Tokyo office and facility operations, vendors, inventory, procurement, and IT assets. Handle local HR administration, onboarding, offboarding, employee expenses, documentation, and compliance. Support Sales through CRM and data tracking, partner outreach, client dinners, venue bookings, and events. Coordinate with headquarters, assist Talent Acquisition, and provide Japanese-English translation while serving as a trusted employee support contact.

Identify and prospect potential app publisher partners, run high-volume outreach, support sales with collateral, maintain Salesforce pipeline, perform market and competitor research, coordinate and staff events, collaborate with marketing, and manage small projects within an international team.

Build and operate scalable Go backend services within adjoe’s distributed adtech platform. Responsibilities include optimizing high-volume production applications, designing Kafka and SQS/SNS-based microservices, aggregating billions of API events, optimizing Druid, MySQL, Redis, and DynamoDB access, integrating machine-learning algorithms, supporting partner-facing APIs, and managing infrastructure with Terraform, Docker, and serverless technologies.

Analyze mobile advertising marketplace performance across bid rates, win rates, timeouts, eCPM, rendering, traffic efficiency, and costs. Design and evaluate A/B tests for product features, pricing, and traffic algorithms; query large datasets with SQL; identify anomalies and optimization opportunities; and build automated BI dashboards for product, engineering, and demand teams. Manage analytics projects and rapid investigations in an agile, fast-paced environment.

Own the product lifecycle for DSP-facing ad exchange capabilities, including roadmap development, auction optimization, traffic shaping, partner integrations, OpenRTB compliance, and metric ownership. Collaborate with engineering, data, demand partnerships, and external DSPs to deliver low-latency, high-throughput adtech features. Lead experimentation, technical requirements, Agile execution, and performance improvements across bidding, routing, monetization, and mobile advertising formats.

Perform manual and exploratory testing across frontend and backend, validate APIs and data using SQL, contribute to UI/API automation (Playwright/Cypress/Postman), document bugs in Jira, participate in sprint planning, and own quality and regression testing before releases.

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.

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.

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.

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.

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.