Role Description Own recommendation, search, ranking, retrieval, and discovery for a consumer content ecosystem. - Build recommendation and search across feed, discovery, search, and content continuation. - Own retrieval and ranking systems, including candidate generation, embeddings, two-tower models, feature engineering, and serving quality. - Design, launch, and analyze recommendation and search experiments. Qualifications - 5+ years of industry experience building production ML systems with senior-level ownership. - Hands-on experience with recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems. - Experience working on consumer applications, entertainment, social media, gaming, creator platforms, or other engagement-driven products. - Strong knowledge of two-tower models, embedding retrieval, candidate generation, ranking systems, and online/offline evaluation. - Fluency in Chinese (Mandarin) is required. Requirements - 5+ years of industry experience building production ML systems with senior-level ownership. - Hands-on experience with recommendation, search, ranking, ads ranking, feed ranking, or content discovery systems. - Experience with consumer applications, entertainment, social, gaming, creator, or engagement-driven products. - Expertise in two-tower models, embedding retrieval, candidate generation, ranking, and online/offline evaluation. Benefits - Built recommendation and search systems across feed, discovery, search, and content continuation. - Owned retrieval and ranking systems, including candidate generation, embeddings, two-tower models, features, and serving quality. - Designed, launched, and analyzed recommendation/search experiments. Culture AI-native, fast-paced startup environment with strong ownership expectations. - Focus on building consumer AI products at the intersection of AI, social, mobile, and interactive entertainment. - Looking for engineers who ship quickly, learn from users, and take end-to-end ownership.

Title: Senior Full Stack Engineer Location: New York, New York|Hybrid|Onsite Job Description: Who is Recruiting from Scratch: Recruiting from Scratch is a specialized talent firm dedicated to helping companies build exceptional teams. We partner closely with our clients to deeply understand their needs, then connect them with top-tier candidates who are not only highly skilled but also the right fit for the company’s culture and vision. Our mission is simple: place the best people in the right roles to drive long-term success for both clients and candidates https://www.recruitingfromscratch.com/ - Location: Onsite, hybrid - Company Stage of Funding: Series B — Software Development - Office Type: Hybrid - Salary: $235k - $250k We're representing an early-stage, mission-driven technology company focused on making the internet a safer place. Founded by individuals who faced the challenges of building scalable Trust and Safety operations, our client is dedicated to equipping teams with advanced tools to effectively protect users and combat online threats. Their platform is integral to the core trust and safety infrastructure used by influential companies globally, tackling issues like misinformation and digital harm. What You Will Do - Design, build, and own backend systems capable of ingesting and processing high-scale, event-driven data from major external platforms. - Lead end-to-end architecture and delivery of significant engineering initiatives, from scoping and design through to production deployment. - Collaborate cross-functionally with product, data, and mission-aligned stakeholders to shape technical direction. - Contribute across the full stack as needed, focusing primarily on backend and systems-level work. - Help establish engineering standards and patterns as the team scales, ensuring high-quality deliverables. - Operate with significant autonomy within a small, highly capable team, making impactful decisions. Ideal Background - 8+ years of professional software engineering experience, with a strong backend foundation and full stack capability. - Proven experience building high-scale or event-driven systems, including real-time data pipelines and message queues. - Track record of owning and leading major engineering projects from problem definition to delivery. - Experience in fast-paced startup environments, demonstrating comfort with ambiguity and a breadth of technical skills. - Genuine mission alignment, motivated by the challenge of enhancing online safety and addressing complex technical problems Preferred - Experience in Trust & Safety, integrity, fraud prevention, or content moderation technology. - Background in 0→1 product building at an early-stage startup. - Exposure to AI/ML, event-driven architectures, or data infrastructure. Compensation and Benefits Our client offers a competitive salary and benefits package, along with the opportunity to work in a high-trust, collaborative environment where your contributions will have a meaningful impact on making the internet safer for everyone.

Role Description The Machine Learning Engineer IV will play a critical role in advancing Jumio's Fraud team's mission to develop and enhance state-of-the-art solutions for fraud detection for ID verification purposes. This role is essential for ensuring the highest standards of security and user verification through the application of advanced machine learning and deep learning techniques, ultimately contributing to Jumio's leadership in the online identity verification, eKYC, and AML solutions market. As a Machine Learning Engineer IV at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in deep learning and computer vision will drive the development of innovative algorithms that keep Jumio at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as Financial Services, Travel, Sharing Economy, Fintech, and Gaming. Your contributions will be pivotal in maintaining Jumio's reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally. - Develop, maintain, and own key fraudulent CV models of Jumio, which shapes the whole fraud product offering of Jumio. - Design and implement machine learning, deep learning, classical CV focused on fraud detection. - Research to support the deployment of the advanced algorithms. - Deploy models as AWS SageMaker endpoints or directly onto devices. - Stay updated with the latest advancements in machine learning, deep learning, and computer vision by engaging with academic papers and attending industry conferences. - Work collaboratively with other engineers and product managers in an Agile development environment. Qualifications - Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field. - A minimum of 6+ years of commercial experience in the field of machine learning/deep learning, not including time spent studying (2 years with Master’s). - Must have: experience with training of DL models for deepfakes, synthetic data, or gen AI data detection. - Deep understanding of how to convert ML metrics to product goals. - Hands-on experience with PyTorch or TensorFlow, SKLearn, and in developing production-grade Python code. - Demonstrated experience in implementing best practices for monitoring and maintaining ML models in production environments. - Strong communication and problem-solving skills. Requirements - Experience in working with LLM’s or VLM’s. - Work with image or video generation. - Experience with cloud environments - AWS / GCP. - Experience in working in global organizations across several timezones. Benefits - IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation. Equal Opportunities Jumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses. Company Description Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders. Jumio is the leading provider of online identity verification, eKYC and AML solutions. With a global footprint, we’re expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others. Applicant Data Privacy We will only use your personal information in connection with Jumio’s application, recruitment, and hiring processes, as described in Jumio’s Applicant Privacy Notice. If you have any questions or comments, please send an email to privacy@jumio.com.

Role Description We are seeking a Senior Middleware Engineer with deep expertise in enterprise messaging, event-driven architecture, and distributed systems integration. In this senior-level role you will be the technical authority for all middleware platforms across the organisation, owning the design, deployment, performance, and reliability of messaging infrastructure that underpins our mission-critical applications. You will lead integration strategy across RabbitMQ, Redis, and Azure Service Bus, working alongside development, DevOps, and cloud architecture teams to deliver scalable, resilient, and observable messaging solutions. You will also serve as the primary escalation point for integration incidents and provide technical leadership and mentoring to the wider engineering team. Key Responsibilities - Architect, deploy, and operate enterprise messaging and middleware platforms including RabbitMQ, Redis, and Azure Service Bus across development, staging, and production environments. - Design and govern event-driven and message-driven integration patterns: pub/sub, competing consumers, dead-letter handling, saga/choreography, and request-reply. - Lead performance engineering for middleware: tune RabbitMQ broker configuration, channel and prefetch settings, Redis eviction policies, cluster topology, and Azure Service Bus namespace tiers and partitioning. - Define and enforce standards for message schema design, versioning, serialisation (JSON, Avro, Protobuf), and backward/forward compatibility. - Implement and maintain High Availability and Disaster Recovery for middleware: RabbitMQ mirrored/quorum queues, Redis Cluster and Sentinel, Azure Service Bus geo-redundancy and paired namespaces. - Establish end-to-end observability: distributed tracing (OpenTelemetry), metrics (Prometheus/Grafana), and alerting for queue depth, consumer lag, connection pool saturation, and error rates. - Collaborate with application development teams to review integration designs, message flow architectures, and service mesh configurations before production release. - Own middleware security posture: TLS configuration, certificate management, RBAC/ACL policies on brokers, Managed Identity authentication for Azure Service Bus, and secrets management. - Drive Infrastructure-as-Code adoption for middleware provisioning using Terraform, Bicep, or Ansible. - Support CI/CD pipeline integration for automated deployment, configuration, and smoke-testing of middleware components. - Lead incident response and post-incident reviews for Severity 1 middleware outages; produce actionable remediation plans. - Mentor mid-level and junior engineers; produce architecture decision records (ADRs), runbooks, and operational documentation. Core Technology Expertise - RabbitMQ - Expert knowledge of AMQP 0-9-1, exchanges, bindings, queues, and routing topologies (direct, topic, fanout, headers). - Experience with Quorum Queues, Lazy Queues, and stream queues for durability and high-throughput scenarios. - RabbitMQ cluster formation, quorum-based leader election, and cross-datacenter federation/shovels. - Management API, Prometheus plugin, and Grafana dashboards for broker observability. - Redis - Deep expertise in Redis data structures: Strings, Hashes, Lists, Sets, Sorted Sets, Streams, and HyperLogLog. - Redis as a message broker: Pub/Sub, Redis Streams with consumer groups, and XREAD/XACK patterns for reliable processing. - Redis as a caching layer: cache-aside, write-through, write-behind, TTL strategies, and cache stampede prevention. - Redis Cluster (hash slots, resharding) and Redis Sentinel for HA; Azure Cache for Redis Premium tier configuration. - Performance tuning: memory optimisation, eviction policies (LRU, LFU, allkeys), persistence (RDB/AOF) trade-offs. - Azure Service Bus - Expert-level experience with Azure Service Bus queues, topics, subscriptions, and forwarding rules. - Message sessions, scheduled messages, deferred messages, dead-letter queues (DLQ), and message lock renewal patterns. - Premium namespace configuration: partitioning, geo-disaster recovery (paired namespaces), and availability zones. - Authentication via Managed Identity (RBAC), Shared Access Signatures (SAS), and Private Endpoints for network isolation. - Integration with Azure Event Grid, Azure Logic Apps, Azure Functions, and APIM for end-to-end integration workflows. - Cost optimisation: right-sizing tiers, auto-delete on idle, and message batching strategies. Required Skills & Experience - 7+ years of software engineering or platform engineering experience, with 4+ years focused on middleware and integration platforms. - Demonstrable senior-level expertise across RabbitMQ, Redis, and Azure Service Bus in production enterprise environments. - Strong understanding of distributed systems fundamentals: eventual consistency, idempotency, at-least-once vs exactly-once delivery, and the two-generals problem. - Experience designing and implementing event-driven microservices architectures and service integration patterns (EIP). - Proficiency in at least one primary programming language commonly used for integration workloads: C# (.NET), Java/Kotlin, Python, or Go. - Hands-on experience with Kubernetes or container orchestration for middleware workloads (Helm charts, operators). - Infrastructure-as-Code experience with Terraform, Bicep, or Ansible for middleware provisioning. - Strong observability skills: distributed tracing with OpenTelemetry, metrics with Prometheus/Grafana, and structured logging. - Experience with secure middleware configuration: TLS/mTLS, certificate rotation, secrets management (Azure Key Vault, HashiCorp Vault). - Proven ability to lead technical initiatives, produce architectural documentation, and mentor engineers. Desirable / Advantageous - Experience with Apache Kafka or Azure Event Hubs for high-throughput event streaming use cases. - Familiarity with Apache Camel, MuleSoft, or Azure Integration Services for enterprise integration patterns. - Microsoft certification: AZ-204 (Azure Developer) or AZ-305 (Azure Solutions Architect). - Experience with service mesh technologies: Istio, Linkerd, or Azure Service Mesh for mTLS and traffic management. - Exposure to CQRS, Event Sourcing, and Outbox Pattern implementations in distributed systems.