Machine Learning Engineer

• We’re building the next generation of intelligent product search—systems that understand user intent, learn from behavior, and continuously improve. As a Senior Python Engineer on our ML/AI Search team, you’ll architect and build the backend services that power product discovery for millions of industrial buyers. Think scalable retrieval pipelines, real time inference, and APIs that make advanced AI usable across the business.
• This is a hands on engineering role—not research. You’ll prototype, ship, and iterate quickly, deploying production systems on GCP and improving them based on real world performance. If you love Python, distributed systems, and search technology, you’ll thrive here.
• What You’ll Work On
• Build & Ship Search + AI Systems
• Design, develop, and deploy end to end Python services—from retrieval and ranking pipelines to customer facing APIs.
• Integrate ML inference pipelines: embeddings, transformer models, LLM powered query understanding, and reranking.
• Build event driven, real time architectures using GCP (Cloud Run, Pub/Sub, GKE, Cloud Functions).
• Own your services in production: testing, observability, monitoring, and on call.
• Shape Our Search Infrastructure
• Partner with Search and ML Architects to build hybrid retrieval systems combining keyword search, vector similarity, and ML reranking.
• Maintain Elasticsearch indexing pipelines, query services, and relevance tuning tools.
• Integrate vector databases (Pinecone, Weaviate, FAISS, etc.) into retrieval workflows.
• Instrument pipelines with meaningful metrics (CTR, zero result rate, latency) to drive A/B experimentation.
• Raise the Engineering Bar
• Champion CI/CD, observability, testing, and infrastructure as code.
• Lead design discussions and translate product requirements into clean, scalable solutions.
• Participate in code reviews and knowledge sharing to elevate the entire team.

• Must Have
• s4+ years of professional backend or full stack engineering experience with a strong Python focus
• .Experience building and deploying cloud native applications (GCP preferred; AWS/Azure welcome)
• .Hands on experience with microservices, REST/gRPC APIs, Docker, Kubernetes, and serverless patterns
• .Strong grounding in software design principles and clean engineering practices
• .Excellent communication skills and comfort working with ML engineers, architects, and product teams
• .Willingness to use AI tools to accelerate development
• .Strongly Preferred (Search + ML Experience
• )Experience with search platforms (Elasticsearch, OpenSearch, Solr, Algolia)
• .Familiarity with vector search concepts and tools (embeddings, ANN, FAISS, Pinecone, Weaviate)
• .Exposure to ML/AI workflows: RAG pipelines, LLM integration, prompt engineering, fine tuning
• .Experience with AI orchestration frameworks (LangChain, LangGraph, Google ADK)
• .Infrastructure as code (Terraform, Pulumi) and mature CI/CD pipeline ownership

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