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ML Search Engineer (Python)

STM Consulting, Inc.

STM Consulting, Inc.
Job Type   /   Job Level
Full-time   /   Others/Any
Job Location
Birmingham, AL
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Job Summary (List Format): Senior Python Engineer, ML/AI Search Team

Core Responsibilities

  • Design, develop, and deploy end-to-end Python backend services for intelligent product search.
  • Integrate and build ML inference pipelines using embeddings, transformer models, and LLMs for query understanding and reranking.
  • Develop scalable retrieval systems, real-time architectures, and customer-facing APIs on Google Cloud Platform (GCP).
  • Own production services including testing, monitoring, observability, and on-call support.
  • Collaborate with Search and ML Architects to create hybrid retrieval systems (keyword, vector similarity, ML reranking).
  • Maintain Elasticsearch indexing pipelines and integrate vector databases (e.g., Pinecone, FAISS) into retrieval workflows.
  • Instrument systems with metrics (CTR, zero result rate, latency) to support A/B testing and experimentation.
  • Champion engineering best practices: CI/CD, infrastructure as code, testing, and observability.
  • Lead technical design discussions and participate in code reviews and team knowledge sharing.

Requirements

  • 4+ years professional backend or full stack engineering experience, with a strong focus on Python.
  • Experience building and deploying cloud-native applications (preferably on GCP; AWS/Azure also welcome).
  • Strong skills in microservices, REST/GRPC APIs, Docker, Kubernetes, and serverless patterns.
  • Solid understanding of software design principles and best engineering practices.
  • Excellent communication; comfortable collaborating with ML engineers, architects, and product teams.
  • Willingness to utilize AI tools to accelerate development.

Preferred Qualifications

  • Experience with search platforms (Elasticsearch, OpenSearch, Solr, Algolia).
  • Familiarity with vector search concepts/tools (embeddings, ANN, FAISS, Pinecone, weaviate).
  • Exposure to ML/AI workflows, such as RAG pipelines, LLM integration, prompt engineering, and fine tuning.
  • Experience with AI orchestration frameworks (LangChain, LangGraph, Google ADK).
  • Proficiency in infrastructure as code (Terraform, Pulumi) and CI/CD pipeline management.
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