Senior ML Search Engineer

Senior ML Search Engineer

Location- Hybrid

Job Summary

STAFFXPERT LLC is seeking a Senior ML Search Engineer on behalf of our client in TBD to build intelligent, scalable product search experiences that understand user intent, leverage behavioral signals, and continuously improve search relevance.

This is a hands-on engineering role focused on taking search and AI/ML solutions from architecture and prototyping through production deployment, monitoring, and continuous optimization. The ideal candidate is an ambitious, self-driven engineer with strong Python, React, API, and search engineering experience who enjoys working across backend, frontend, ML, and cloud technologies.

Key Responsibilities

• Design, develop, and deploy production-grade search, retrieval, ranking, and AI/ML systems .

• Build scalable Python services, microservices, and RESTful/gRPC APIs .

• Develop hybrid search solutions combining keyword search, vector retrieval, semantic search, and reranking.

• Build and maintain Elasticsearch/OpenSearch indexing, query, and relevance-tuning pipelines.

• Develop ML inference capabilities using embeddings, transformer-based models, classifiers, and LLM-powered query understanding.

• Integrate vector search technologies such as FAISS, Pinecone, Weaviate , or similar platforms.

• Build responsive, production-ready React interfaces and reusable frontend components.

• Develop event-driven and real-time architectures using cloud-native services.

• Monitor and optimize search performance using metrics such as CTR, zero-result n/a, relevance, conversion, and latency .

• Apply search analytics and experimentation to continuously improve relevance and user experience.

• Champion automated testing, CI/CD, observability, and infrastructure-as-code practices.

• Participate in architecture and technical design discussions and translate business requirements into scalable solutions.

• Conduct code reviews, share knowledge, and mentor junior and mid-level engineers.

• Own applications and services throughout their lifecycle, including deployment, monitoring, troubleshooting, and production support.

Required Qualifications

• 6+ years of professional software engineering experience.

• Strong hands-on expertise with Python and React .

• Proven experience developing production-grade backend or full-stack applications.

• Strong experience building and integrating RESTful and/or gRPC APIs .

• Experience working within a monorepo or large multi-service codebase .

• Professional experience with Elasticsearch, OpenSearch, Solr, Algolia , or similar search platforms.

• Strong understanding of search concepts including indexing, query DSL, relevance tuning, ranking, and search analytics.

• Experience with vector search, embeddings, semantic search, or approximate nearest-neighbor (ANN) retrieval .

• Experience designing scalable, resilient, high-throughput services.

• Strong knowledge of asynchronous programming, type annotations, testing, and software design principles.

• Experience with Docker and Kubernetes .

• Experience designing and deploying cloud-native applications; GCP experience is strongly preferred .

• Experience with relational and NoSQL databases such as PostgreSQL, MySQL, Oracle, MongoDB, or DynamoDB.

• Strong understanding of SOLID principles, design patterns, and engineering best practices .

• Excellent communication and collaboration skills.

• Ability to work effectively with engineers, architects, ML teams, and product stakeholders.

• Demonstrated ability to learn new technologies quickly and solve complex engineering problems independently.

Preferred Qualifications

• Experience with RAG, LLM integration, prompt engineering, model inference, or fine-tuning .

• Experience with LangChain, LangGraph, Google ADK , or similar AI orchestration frameworks.

• Experience with modern React frameworks such as Next.js, Vite, Remix, or Gatsby .

• Experience with Terraform, Pulumi, OpenTofu , or other Infrastructure-as-Code tools.

• Experience owning mature CI/CD pipelines and cloud infrastructure .

• Experience with search A/B testing, experimentation, and relevance optimization.

• Experience with AI-assisted software development tools.

• Prior experience mentoring engineers and contributing to engineering standards.