AI/ML Research Engineer

3 days ago

Bangalore, India Hiver Full time
Hiver offers teams the simplest way to offer outstanding and personalized customer service. As a customer service solution built on Gmail, Hiver is intuitive, super easy to learn, and delightful to use. Hiver is used by thousands of teams at some of the best-known companies in the world to provide attentive, empathetic, and human service to their customers at scale. Our product is loved by our customers, our content engages a very wide audience, our customer service is one of the highest rated in the industry, and our sales team is as driven about doing right by our customers as they are by hitting their numbers. K1 Capital led our most recent round of $27 million. Before that, we raised from Kalaari Capital, Kae Capital, and Citrix Startup Accelerator. Opportunity: As a Software Development Engineer III at Hiver, you will build and scale backend systems that power both traditional workflows and AI-driven features. Own low-latency, cost-efficient AI endpoints and data pipelines.
Integrate intelligent workflows into existing services with measurable impact.
Mentor engineers and raise engineering standards.

Make the architecture scalable for growing traffic and AI workloads.
Build frameworks to monitor, improve, and optimize AI-backed systems.
Improve reliability, latency, and performance of both traditional and AI services.
Implement AI components: model serving, inference/generation APIs, retrieval/RAG, embeddings, rerankers, vector stores.
Stand up evaluation + guardrails: test sets, canaries, A/B, drift detection, content safety, fallback chains.
Build secure storage and processing for large-scale structured/unstructured data; enforce data contracts.
Debug production issues across services and layers; lead incident response and postmortems.
Collaborate with AI/ML engineers and data scientists to productionize models and notebooks.
Strong experience scaling backend/distributed systems and microservices.
deep understanding of reliability, performance, and resiliency.
high-volume data pipelines.
Hands-on SQL; exposure to vector databases preferred.
Solid in one or more of Go/Java/Python ; high-quality, maintainable code.
Cloud deployment (AWS preferred; Security and privacy fundamentals for PII and prompt/content safety.
Prior collaboration with AI/ML teams from research to production is desirable.

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