Software Engineer, ML Inference Platform

Dialpad · Buenos Aires, Argentinamid

En corto

▸Construir sistemas de inferencia de IA escalables en GPU en GCP para modelos internos.
▸Trabajar en optimización de rendimiento, despliegue seguro y gestión de tráfico low-latency.
▸Ser parte de un equipo nuevo que define la infraestructura crítica para producción de IA.

Fluent English required for collaboration and documentation.

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¿Qué piden?

✓Experiencia en ingeniería de sistemas para inferencia de modelos de IA.
✓Conocimiento avanzado en GPUs y optimización de rendimiento en entornos cloud.
✓Habilidades en diseño y desarrollo de servicios de bajo latency.
✓Experiencia con GCP y servicios relacionados (GKE, Cloud Storage, etc).
✓Capacidad para construir sistemas observables y escalables.
✓Trabajo colaborativo en un entorno de alta velocidad y de alto impacto.

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GCPNVIDIA GPUsGKEKubernetesPythonBazelgRPCPrometheusOpenTelemetryBash

¿A quién escribirle en Dialpad?

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About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role We are hiring ML Inference Platform Engineers to build the production systems that serve our in-house AI models at scale. This role sits at the intersection of model development, high-performance runtime systems, and cloud infrastructure. You will help turn trained models and emerging AI capabilities into reliable, observable, low-latency production services running on NVIDIA GPUs in GCP. This is not a research role, and it is not a generic MLOps or support role. It is an implementation-heavy systems engineering role focused on the machinery of inference: model serving, runtime optimization, GPU utilization, deployment safety, traffic management, benchmarking, and production reliability. Our mission is to shorten the path from promising model capability to dependable production impact. We build the shared infrastructure, standards, and release pathways that allow models to move from candidate artifacts into scalable, rollback-safe inference services with clear performance, reliability, and cost characteristics. This is a new team, so the systems and interfaces

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