Senior Backend Engineer: Machine Learning Infrastructure
Core
Build and operate scalable backend services, data pipelines, and platform capabilities enabling ML teams to develop, deploy, and run models (including LLMs) reliably at scale.
Role type
Senior Backend Engineer (ML Infrastructure)
Builds
Distributed backend services, APIs, data pipelines, and self-service infrastructure for ML workloads
Domain
Cloud infrastructure, distributed systems, machine learning platforms
Deliverable
infrastructure
Required skills
Python, distributed systems engineering, cloud platforms (AWS/GCP/Azure), Kubernetes, system design, observability, API development
Preferred skills
Rust/C/C++/Go, vector databases (Qdrant/Milvus/Weaviate/OpenSearch/pgvector), model serving/inference, Infrastructure as Code (Terraform), ML platform development
Technologies
Python, AWS, GCP, Azure, Kubernetes, Terraform, Qdrant, Milvus, Weaviate, OpenSearch, pgvector
Responsibilities
Design and operate high-load distributed backend services and APIs; own end-to-end lifecycle of core ML services and data pipelines; build reusable infrastructure components; partner with ML/product teams to translate requirements into platform capabilities; evaluate architectural trade-offs and make technical decisions; maintain service reliability, performance, and observability; proactively resolve technical and operational problems
Seniority
Senior, hands-on IC