High 5 Games

Marketing

• Campaign management: Set up, monitor, and optimize paid ad campaigns on platforms such as Facebook, Instagram, and others within the Meta ecosystem.
• Budget management: Allocate and manage ad spend to ensure campaigns stay within budget and achieve objectives.
• Audience targeting: Define and target specific audiences based on demographics, interests, and behaviors.
• Performance analysis: Analyze campaign data to understand what is working and what is not.
• Optimization: Adjust targeting, bidding strategies, and ad creatives based on performance data to improve results and ROI.
• Reporting: Prepare and deliver performance reports, updating spreadsheets and tracking key metrics.
• Troubleshooting: Identify and fix issues that may block campaign growth or performance.
• Maintain required documentation: (recruiting tracker, ATS – interview notes, etc.) and report progress to management.
• Performs other related duties as assigned.

Media Buyer

Marketing Analyst

• Support the launch and monitoring of marketing campaigns across email, push, in-app, and paid acquisition channels (social, display, influencer)
• Help set up and test automated customer journeys that welcome, reactivate, or retain players—at scale
• Assist with building data-driven models using AI tools to improve player segmentation, bonus recommendations, and creative testing
• Support user acquisition reporting, including CPA tracking, creative performance, and install flow data
• Help evaluate churn behavior and identify high-potential segments using first-party data and event logs
• Contribute to A/B tests across acquisition and lifecycle campaigns to drive continuous optimization
• Work with Product, Analytics, Creative, and Paid Media teams to help execute coordinated marketing efforts
• Track CRM and UA trends across the gaming and sweepstakes landscape—bringing fresh ideas to the table

DevOps Engineer

• Manage, configure, and automate cloud infrastructure using tools such as Terraform and Ansible.
• Implement CI/CD pipelines for ML models and data workflows, focusing on automation, versioning, rollback, and monitoring with tools like Vertex AI, Jenkins, and DataDog.
• Build and maintain scalable data and feature pipelines for both real-time and batch processing using BigQuery, BigTable, Dataflow, Composer, Pub/Sub, and Cloud Run.
• Set up infrastructure for model monitoring and observability — detecting drift, bias, and performance issues using Vertex AI Model Monitoring and custom dashboards.
• Optimize inference performance, improving latency and cost-efficiency of AI workloads.
• Ensure overall system reliability, scalability, and performance across the ML/Data platform.
• Define and implement infrastructure best practices for deployment, monitoring, logging, and security.
• Troubleshoot complex issues affecting ML/Data pipelines and production systems.
• Ensure compliance with data governance, security, and regulatory standards, especially for real-money gaming environments.

DevOps Engineer – ML & Data Infrastructure

Data Scientist

• Design, implement, and maintain robust data pipelines, from event generation through ETL to clean, intelligent storage.
• Retrieve, process, and integrate data using APIs and webhooks, ensuring quality, accuracy, and integrity at every step.
• Develop reporting layers—dashboards, automated reports, and notifications—to deliver insights across teams.
• Curate raw data into meaningful structures for CRM, product, and monetization teams.
• Build predictive and optimization models for areas like player lifetime value, churn prediction, monetization strategies, and game recommendations.
• Define and execute multivariate testing frameworks to optimize product and campaign performance.
• Explore and apply state-of-the-art AI and ML techniques, in real-time processes, proposing innovative approaches for real-world challenges.
• Deeply understand and navigate the abstract mechanics of our ecosystem—game economies, monetization levers, RTPs, and more.

Junior Data Scientist

Customer Support

• Respond to customer inquiries via various communication channels (phone, email, chat, or social media).
• Listen attentively to customer concerns and provide accurate and timely responses.
• Maintain a professional and empathetic demeanor when addressing customer issues.
• Analyze customer problems and troubleshoot issues effectively.
• Follow established procedures to resolve customer complaints or escalate complex issues to higher-tier support.
• Collaborate with other teams or departments to find solutions to customer concerns.
• Acquire in-depth knowledge of the company's products or services to provide informed assistance to customers.
• Stay updated on product/service updates, changes, and promotions.
• Maintain detailed records of customer interactions, including complaints, inquiries, and resolutions.
• Assist customers with technical issues related to products or services.
• Communicate with customers clearly and effectively, using professional and courteous language.
• Follow up with customers to ensure their issues are fully resolved and their needs are met.

Customer Support Agent

Social Media Manager

• Develop and execute a comprehensive social media strategy that aligns with brand and goals.
• Create and curate engaging and visually appealing content, including text, images, videos, and infographics.
• Research industry trends, crypto news, and online gaming developments to create timely and relevant content.
• Engage with our community on a variety of platforms including Discord and Telegraph, respond to comments and messages, and foster positive interactions across various social media accounts.
• Collaborate with the marketing team to plan and execute social media campaigns, contests, and promotions.
• Track and analyze key performance metrics to measure the effectiveness of social media efforts and make data-driven improvements.
• Monitor competitor activities and identify opportunities for differentiation and growth.

Social Media Coordinator

Operations

• Oversee B2C Operations group
• Lead Fraud, Risk, and Payments team
• Develop and implement fraud and risk management strategies
• Collaborate cross-functionally with various departments
• Automate manual processes
• Review business rules and analyze transactional data
• Ensure compliance with regulations

Operations Manager, Fraud & Payments

• Shape and execute a social media strategy that keeps our community buzzing and our brand top-of-mind.
• Create content people actually want to share. From posts and memes to videos and infographics.
• Keep track of industry trends, crypto news, and igaming culture to post content that feels fresh and relevant.
• Jump into conversations, reply to messages, and keep our community spaces fun and welcoming.
• Team up with marketing to roll out campaigns, contests, and promotions.
• Track and analyze key performance metrics to measure the effectiveness of social media efforts and make data-driven improvements.
• Keep an eye on competitors and find creative ways to stand out in the crowd.

Social Media and Community Coordinator

Engineer

• Design, develop, and deploy machine learning models and solutions
• Collaborate on building and maintaining scalable data and feature pipeline infrastructure
• Develop and implement robust strategies for model monitoring and observability
• Optimize ML model inference performance
• Ensure the overall reliability, performance, and scalability of the ML models
• Troubleshoot and resolve complex issues impacting ML models
• Ensure AI/ML models and workflows meet data governance, security, and compliance requirements

Machine Learning Engineer – Agentic Focus

• Design, develop, and deploy machine learning models and solutions, leveraging tools such as LangGraph and MLflow for orchestration and lifecycle management.
• Collaborate on building and maintaining scalable data and feature pipeline infrastructure for real-time and batch processing using tools like BigQuery, BigTable, Dataflow, Composer(Airflow), PubSub, and Cloud Run to support ML model training and inference.
• Develop and implement robust strategies for model monitoring and observability to detect model drift, bias, and performance degradation, leveraging tools like Vertex AI Model Monitoring and custom dashboards.
• Optimize ML model inference performance to improve latency and cost-efficiency of AI applications.
• Ensure the overall reliability, performance, and scalability of the ML models and data infrastructure platform, including proactive identification and resolution of issues related to model performance and data quality.
• Troubleshoot and resolve issues impacting ML models, data pipelines, and production AI systems.
• Ensure AI/ML models and workflows meet data governance, security, and compliance requirements, specifically for real-money gaming.

Junior Machine Learning Engineer – Agentic Focus

• Design, implement, and maintain robust data pipelines, from event generation through ETL to clean, intelligent storage.
• Retrieve, process, and integrate data using APIs and webhooks, ensuring quality, accuracy, and integrity at every step.
• Develop reporting layers—dashboards, automated reports, and notifications—to deliver insights across teams.
• Curate raw data into meaningful structures for CRM, product, and monetization teams.
• Build predictive and optimization models for areas like player lifetime value, churn prediction, monetization strategies, and game recommendations.
• Define and execute multivariate testing frameworks to optimize product and campaign performance.
• Explore and apply state-of-the-art AI and ML techniques, in real-time processes, proposing innovative approaches for real-world challenges.
• Partner and influence cross-functional teams—including CRM, Server, Data Engineering, and Leadership—to implement end-to-end solutions quickly and effectively.
• Align data projects with business goals and ROI considerations, applying pragmatic 80/20 thinking to maximize impact.
• Deeply understand and navigate the abstract mechanics of our ecosystem—game economies, monetization levers, RTPs, and more.

Senior Data Scientist

Backend Engineer

• Design, develop, and optimize highly scalable Java-based backend systems and microservices
• Build and maintain real-time, high-throughput architectures using Spring Boot (2.5+), REST APIs, Tomcat, Kubernetes, and the Docker ecosystem
• Design and deliver high-volume, highly available back-end infrastructures (20K+ mps) leveraging Kafka and Hazelcast
• Apply distributed system concepts such as leadership, consensus, partitioning, and replication to ensure scalability and resilience
• Conduct performance analysis and optimization across databases, application code, and infrastructure layers
• Develop comprehensive testing strategies (TDD, BDD) and ensure code reliability through robust unit, integration, and system tests
• Identify, diagnose, and resolve complex production issues with strong debugging and troubleshooting skills
• Work with both SQL and NoSQL databases, particularly Cassandra and MySQL
• Utilize cloud-based big data tools for data processing and analysis
• Implement real-time stream analysis and contribute to machine learning (ML) and AI modeling initiatives where applicable
• Build operationally mature systems that are scalable, secure, and well-instrumented
• Use tools like Gradle, Jenkins, Nexus, GCP, Kubernetes, Docker, and Datadog for CI/CD, monitoring, and deployment
• Apply SDLC best practices and ensure code quality, documentation, and smooth delivery pipelines
• Collaborate using Jira, Confluence, and other tools to maintain alignment across teams.

Senior Server Engineer

• Manage, configure, and automate cloud infrastructure using tools like Terraform, Terragrunt, and Ansible.
• Implement and maintain CI/CD pipelines for reliable, repeatable deployments using tools such as Jenkins and Datadog.
• Leverage Google Cloud Platform (GCP) to build scalable and highly available systems.
• Manage and optimize virtualized environments using VMware vSphere.
• Orchestrate containerized applications with Kubernetes and manage containers with Docker.
• Maintain build artifacts using Nexus Repository Manager.
• Collaborate with teams via Bitbucket Cloud, Jira, and Confluence to ensure alignment and visibility.
• Monitor infrastructure and application performance using Datadog and Sentry for real-time error tracking and observability.
• Continuously look for ways to improve automation, reliability, and deployment speed across environments.