What are the responsibilities and job description for the ML Search Engineer (Python) position at STM Consulting, Inc.?
Job Summary (List Format): Senior Python Engineer, ML/AI Search Team
Core Responsibilities
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.
- 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.
- 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.