Senior ML Search Engineer - Full-Stack & Cloud

Deploy; Birmingham (AL); On-site; USD 120,000 - 180,000; Full time

Job summary

Deploy is seeking a Search Engineer (Software Engineer III) to own end-to-end product search systems, blending frontend and backend work on GCP. You will work on retrieval pipelines, embeddings, and vector databases, collaborating with ML and product teams.

The role emphasizes production-grade services, observability, and CI/CD, with opportunities to influence search infrastructure and frontend architecture. Strong Python and React fundamentals and cloud-native delivery are essential.

Qualifications

• 5+ years of backend or full-stack engineering experience.
• Strong Python and React experience with production-grade services.
• Cloud-native applications on GCP/AWS.
• Experience with microservices and RESTful APIs.
• Familiarity with search systems and vector databases is a plus.
• Experience with CI/CD and observability.

Responsibilities

• Design, develop, and deploy Python services end-to-end—from retrieval and ranking pipelines to APIs.
• Build ML inference pipelines (embeddings, transformers, LLM querying, reranking).
• Develop real-time architectures on GCP (Cloud Run, Pub/Sub, GKE, Functions).
• Write tested, observable backends; own services from deployment to monitoring.
• Drive frontend architecture decisions and create reusable components.
• Collaborate with ML/Architects on hybrid retrieval and indexing pipelines.
• Contribute to code reviews and knowledge sharing.

Skills

Python backend

React frontend

Cloud-native architecture

RESTful APIs

Microservices

Docker

Kubernetes

CI/CD

Monorepos

Databases (Relational/NoSQL)

Mentorship

Search systems

AI tooling awareness

Tools

GCP

Elasticsearch/OpenSearch

FAISS / Pinecone

LangChain / LangGraph

Terraform

Job description

Deploy is seeking a Search Engineer (Software Engineer III) to own end-to-end product search systems, blending frontend and backend work on GCP. You will work on retrieval pipelines, embeddings, and vector databases, collaborating with ML and product teams.

The role emphasizes production-grade services, observability, and CI/CD, with opportunities to influence search infrastructure and frontend architecture. Strong Python and React fundamentals and cloud-native delivery are essential.