TL;DR

Staff Engineer, Machine Learning (AI): Design and build backend services powering AI/ML runtime, including orchestration, session/state management, and tools/services integration, with an accent on implementing end-to-end retrieval and memory systems. Focus on performance, reliability, and cost optimization with strong SLO ownership and observability practices.

Location: Service Region: South Asia

Company

%hirify_global% is a Digital Product Engineering company building products, services, and experiences.

What you will do

Design and build core backend services powering AI/ML runtime including orchestration, session/state management, and tools/services integration.
Implement end-to-end retrieval and memory systems covering ingestion, embeddings, indexing, vector search, ranking, caching, and lifecycle management.
Productionize ML workflows with feature/metadata services, model integration contracts, and evaluation hooks.
Drive performance, reliability, and cost optimization with strong SLO ownership and observability practices (logs, metrics, tracing, guardrails).
Collaborate with applied ML teams on model routing, prompts/tools, evaluation datasets, and safe releases.
Translate business requirements into scalable technical designs, define NFR benchmarks, and review architecture for extensibility and best practices.

Requirements

Total experience of 6 years+.
Strong expertise in Python and backend engineering with experience building scalable, distributed microservices.
Hands-on experience designing and delivering end-to-end RAG (Retrieval-Augmented Generation) workflows in production systems.
Solid understanding of ML solution design, including embeddings, retrieval, ranking, feature engineering, and evaluation strategies.
Experience with vector databases (FAISS, Pinecone, Milvus, Weaviate) and implementing chunking, indexing, vector search, re-ranking, caching, and memory patterns.
Strong backend integration skills using REST/gRPC APIs, Docker, Kubernetes, CI/CD, and cloud platforms (AWS/GCP/Azure).

Qualifications

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.