Mayflower

• Perform firmware updates and lifecycle management for server hardware • Troubleshoot hardware and infrastructure-related issues (servers, components, connectivity) • Support provisioning and decommissioning of bare metal servers • Work with out-of-band management interfaces (IPMI / iDRAC / iLO or similar) • Apply and maintain hardware configuration standards and profiles • Participate in incident response and root cause analysis • Contribute to development of operational processes and documentation (SOPs) • Collaborate with infrastructure, network and devops teams • Participate in evaluation and selection of hardware configurations (CPU, RAM, storage, components) • Contribute to infrastructure scaling and hardware standardization • Participate in on-call rotations

• Conduct keyword research and analyze search intent, SERP structure, and competitor performance to identify organic growth opportunities; • Optimize existing pages and create SEO recommendations for titles, meta descriptions, headings, internal links, page structure, and content; • Develop SEO briefs, keyword maps, and content guidelines to support content planning; • Identify technical SEO issues (crawling, indexing, redirects, canonicals, page speed, internal linking) and implement fixes; • Monitor and report on organic performance using tools such as GSC, GA4, Ahrefs, Semrush, or Screaming Frog; • Identify CRO opportunities from organic traffic and support conversion improvement initiatives; • Stay current with SEO best practices and search engine algorithm updates; • Create wireframes and handle basic design tasks in Figma; plan site structure and prepare landing pages; • Implement structured data and schema markup.

Role Description We are looking for a Machine Learning Lead (Engineering) focused on building and delivering production-grade ML-powered applications. This role is not about research or experimentation. You will be responsible for turning ML models into reliable, scalable, user-facing services. You will work at the intersection of machine learning and backend engineering, owning the full lifecycle of ML-powered features — from integration to deployment and operation in production. Job Responsibilities - Design and build production ML services (APIs, microservices, real-time systems) - Integrate ML models into user-facing applications - Ensure reliability, scalability, and performance of ML-powered systems - Define and implement best practices for serving, versioning, and monitoring models in production - Collaborate closely with: - ML engineers / data scientists (who develop models) - DevOps / MLOps team (who provide platform and infrastructure) - Own the delivery pipeline of ML features into production - Lead and mentor engineers working on ML-powered applications - Drive architectural decisions around low-latency and high-load systems - Identify bottlenecks between experimentation and production and eliminate them Qualifications - 5+ years of experience in software engineering / ML engineering - Strong experience building production backend systems (Python preferred) - Hands-on experience deploying and serving ML models in production - Experience with API development (FastAPI, Flask, gRPC, etc.) - Understanding of system design, scalability, and high-load environments - Experience working with ML pipelines and model lifecycle - Ability to bridge the gap between ML and engineering teams - Experience in a Lead or Senior role (mentoring, ownership, decision-making) Requirements - Experience with real-time ML systems (recommendations, ranking, personalization) - Experience in video streaming or high-throughput platforms - Familiarity with Kubernetes and cloud/on-prem environments - Experience with feature stores, model monitoring, A/B testing - Experience working alongside MLOps platforms (MLflow, Airflow, etc.) Benefits - Full remote work - Competitive compensation with a service contract - Transparent performance reviews twice a year, with bonus opportunities and salary adjustments - An annual allowance for home office improvements, sports activities, equipment upgrades, and more - Investment in your development: paid language courses, access to various learning platforms, and a mindfulness benefit, including psychological support with 50% coverage - Career growth in a fast-scaling project with opportunities to influence technical decisions - A culture of recognition: our peer reward program celebrates contributions from across the team

Role Description We are looking for a Lead Machine Learning Engineer focused on building and delivering production-grade ML-powered applications. This role is not about research or experimentation. You will be responsible for turning ML models into reliable, scalable, user-facing services. You will work at the intersection of machine learning and backend engineering, owning the full lifecycle of ML-powered features — from integration to deployment and operation in production. - Design and build production ML services (APIs, microservices, real-time systems) - Integrate ML models into user-facing applications - Ensure reliability, scalability, and performance of ML-powered systems - Define and implement best practices for serving, versioning, and monitoring models in production - Collaborate closely with: - ML engineers / data scientists (who develop models) - DevOps / MLOps team (who provide platform and infrastructure) - Own the delivery pipeline of ML features into production - Lead and mentor engineers working on ML-powered applications - Drive architectural decisions around low-latency and high-load systems - Identify bottlenecks between experimentation and production and eliminate them Qualifications - 5+ years of experience in software engineering / ML engineering - Strong experience building production backend systems (Python preferred) - Hands-on experience deploying and serving ML models in production - Experience with API development (FastAPI, Flask, gRPC, etc.) - Understanding of system design, scalability, and high-load environments - Experience working with ML pipelines and model lifecycle - Ability to bridge the gap between ML and engineering teams - Experience in a Lead or Senior role (mentoring, ownership, decision-making) Requirements - Experience with real-time ML systems (recommendations, ranking, personalization) - Experience in video streaming or high-throughput platforms - Familiarity with Kubernetes and cloud/on-prem environments - Experience with feature stores, model monitoring, A/B testing - Experience working alongside MLOps platforms (MLflow, Airflow, etc.) Benefits - Full remote work - Competitive compensation with a service contract - Transparent performance reviews twice a year, with bonus opportunities and salary adjustments - An annual allowance for home office improvements, sports activities, equipment upgrades, and more - Investment in your development: paid language courses, access to various learning platforms, and a mindfulness benefit, including psychological support with 50% coverage - Career growth in a fast-scaling project with opportunities to influence technical decisions - A culture of recognition: our peer reward program celebrates contributions from across the team

• Perform firmware updates and lifecycle management for server hardware • Troubleshoot hardware and infrastructure-related issues (servers, components, connectivity) • Support provisioning and decommissioning of bare metal servers • Work with out-of-band management interfaces (IPMI / iDRAC / iLO or similar) • Apply and maintain hardware configuration standards and profiles • Participate in incident response and root cause analysis • Contribute to development of operational processes and documentation (SOPs) • Collaborate with infrastructure, network and devops teams • Participate in evaluation and selection of hardware configurations (CPU, RAM, storage, components) • Contribute to infrastructure scaling and hardware standardization • Participate in on-call rotations

• Form and develop a thriving Japanese-speaking community. • Attract new members and ensure an inclusive, vibrant atmosphere. • Attend offline events and engage with community members face-to-face. • Moderate and manage existing Discord channel. • Actively interact in chats, help onboard new members, and provide friendly support. • Gather and share user feedback to improve our platform’s functionality. • Prevent and resolve community conflicts with professionalism. • Monitor community metrics and conduct engagement activities to foster participation.

• Deliver adequate monitoring and failsafe solutions(HA, DRP) for OpenStack cloud. • Support and scale company. • Internal OpenSource cloud solution. • Infrastructure services, such as: Proxies, DNS, caches, gateways, etc. • Prometheus\VictoriaMetrics. • Roles\chars\modules for IaC (Ansible, Terraform). • CI/CD for cloud provision.

• Developing new payment integrations and services; • Automating and optimizing integration processes; • Analyzing external provider documentation and defining epics and tasks; • Participating in the design and development of high-load system architectures; • Supporting and improving existing solutions and services; • Writing high-quality, test-covered code; • Conducting code reviews; • Optimizing system performance and database queries; • Analyzing and resolving production incidents and bugs; • Collaborating with the QA team to ensure high quality of delivered products; • Maintaining technical documentation and writing technical specifications.

• Developing new payment features and services. • Designing and implementing APIs (external and internal). • Creating and maintaining processes in Camunda. • Participating in the design and development of high-load system architectures. • Supporting and enhancing existing solutions and services. • Writing high-quality, test-covered code (unit tests, integration tests). • Conducting code reviews, including frontend code. • Optimizing system performance and database queries. • Analyzing and resolving production incidents and bugs. • Processing and resolving requests from technical support and users as part of daily duties. • Collaborating with the QA team to ensure the high quality of the delivered product. • Maintaining technical documentation and writing technical specifications. • Assisting in onboarding new developers and ensuring code quality. • Participation in the creation of business epics — analyzing requirements, assessing feasibility, and proposing alternative or optimized solutions based on technical expertise.

• Own and deliver high-quality copy across Brand Marketing touchpoints, including brand campaigns, CRM, social, product marketing, PR, and community channels; • Write clear, engaging, and distinctive copy that aligns with the brand voice and resonates with target audiences; • Take ownership of copy development from brief through to final delivery, ensuring speed, quality, and consistency; • Develop and maintain a clear, accessible tone of voice framework for the brand, ensuring it is consistently applied across all Brand Marketing outputs; • Review and elevate existing copy, rewriting where needed to bring it up to brand standard; • Work closely with Design and Creative to develop integrated campaign ideas and ensure copy and visuals work seamlessly together; • Contribute to brand campaigns and key moments throughout the year, developing strong concepts, headlines, and messaging; • Support product marketing campaigns by translating features and updates into clear, engaging, and on-brand messaging; • Ensure all copy is aligned with brand vision and strategy, maintaining a high bar for quality across all outputs; • Take ownership of copy quality across Brand Marketing, reducing the need for senior rewrites and rework; • Use AI tools effectively to scale copy production while maintaining a high standard of quality, creativity, and brand consistency.