Jobs at Metropolis Technologies

Lead the technical vision of ML Engineering, overseeing data infrastructure, ML pipelines, and team management to transition AI models into production.

As a Senior Machine Learning Engineer, you will design and deploy computer vision models, collaborate with teams, and mentor juniors while ensuring high-performance solutions.

Design, develop, and maintain scalable backend services in Java and Scala; implement gRPC APIs; use Redis, MySQL/PostgreSQL and Kafka for low-latency data and event streaming; deploy and manage microservices on Kubernetes; collaborate with Hardware, ML, and Operations teams; diagnose and resolve performance and scalability issues.

Lead application and product security across web, mobile, API, AI/CV, and cloud-native systems. Drive secure SDLC, DevSecOps, CI/CD and supply chain security, threat modeling, tooling/automation, vulnerability remediation, and developer enablement while partnering closely with engineering teams.

Senior Cloud Infrastructure Engineer responsible for designing, building, and operating central cloud infrastructure on AWS; managing observability (Datadog), version control and CI/CD (Git/GitHub); and collaborating closely with product and engineering teams. Role requires regular on-site presence (four days/week) and contributes to platform reliability and scalability.

Lead technical vision and cross-team initiatives for Network Expansion, architecting and delivering distributed, customer-facing systems. Manage and coach multiple engineering teams, collaborate with product/design/operations, own business outcomes, and improve CI/CD, testing, and production reliability.

Lead and build the Finance Business Intelligence function: set strategy, hire and grow a multidisciplinary data team, evolve reporting into predictive and AI-augmented analytics, govern finance data and metrics, partner with Finance leadership, and select the finance data stack and tools to deliver scalable, auditable, and trustworthy analytics and forecasting.

Lead the Applied AI organization, architect AI-focused operating models, manage a team of AI engineers, and redesign business processes for improved efficiency and cost savings.

Lead large cross-functional vision system programs integrating hardware, ML, platform, and product teams. Scope and deliver projects, align internal/external partners, translate customer needs into requirements, troubleshoot field systems, evaluate tradeoffs, mitigate risks, and communicate strategy to technical and non-technical stakeholders to scale vision solutions.

The Senior AI Engineer will design and build AI-powered automation tools, maintain LLM systems, and collaborate with business analysts to enhance processes across various operations.

The Senior Software Engineer will architect and build Metropolis Web Services, focusing on distributed systems and platform infrastructure, optimizing performance, and enabling seamless communication and reliability for various services.

Serve as primary relationship manager for airline clients and vendor couriers, overseeing day-to-day operations, SLAs, and escalations. Produce QBRs and performance reports, leverage data and AI to improve logistics and ETA accuracy, partner with Product and Engineering on feature requests, and optimize vendor courier networks to drive operational efficiency and customer satisfaction.

Serve as primary relationship manager for airline clients and vendor couriers in baggage logistics. Oversee day-to-day vendor operations, enforce SLAs, lead QBRs, translate data into insights, handle escalations, and partner with Product and Engineering to implement AI-driven operational improvements.