ML Search Engineer

Genuine Parts Company; Alabama; On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Healthcare coverage

401(k)

Tuition reimbursement

Vacation, sick, and holiday pay

Job summary

Genuine Parts Company is looking for a Search Engineer to lead the development of intelligent product search systems. In this role, you'll design and build backend systems that improve product discovery for users. Strong Python skills and cloud-native experience, especially with GCP, are essential.

The successful candidate will engage in full lifecycle development, leveraging AI and machine learning technologies.

Qualifications

• 4+ years of professional backend or full-stack engineering experience.
• Experience deploying cloud-native applications.
• Familiarity with vector search concepts.

Responsibilities

• Design, develop, and deploy production Python services.
• Build and integrate ML inference pipelines.
• Lead design sessions with Engineering teams.

Skills

Strong Python foundation

Cloud-native experience

Hands-on experience building microservices

Solid understanding of containerization

Good communicator

Tools

GCP

Docker

Kubernetes

Elasticsearch

Job description

Overview

Search Engineer (Software Engineer III)

You must be eligible to work in the US without Visa Sponsorship.

About the role

We're building intelligent product search that understands intent, learns from behavior, and gets smarter over time. As a Senior Python Engineer on the ML/AI Search team, you'll design and build the backend systems that power product discovery for millions of industrial buyers—from scalable retrieval pipelines to the APIs and interfaces that make AI accessible.

This isn't a research role. You'll own the full lifecycle: prototyping ideas, shipping production-grade services on GCP, and iterating based on real user data. Strong Python engineering is the foundation—if you also bring experience in search systems, vector databases, or Elasticsearch, you'll hit the ground running from day one.

What you’ll do

Build & Ship Search and AI-Powered Systems

• Design, develop, and deploy production Python services end-to-end—from retrieval and ranking pipelines through client-facing APIs.
• Build and integrate ML inference pipelines: embedding models, transformer-based classifiers, LLM-powered query understanding, and reranking services.
• Develop event-driven, real-time architectures using GCP services—Cloud Run, Pub/Sub, GKE, Cloud Functions.
• Write clean, well-tested, observable Python backends; own your services through deployment, monitoring, and on-call

Contribute to Search Infrastructure

• Work alongside the Search Architect and ML Architect to implement hybrid retrieval systems combining keyword search, dense vector similarity, and reranking.
• Build and maintain Elasticsearch indexing pipelines, query services, and relevance tuning tooling.
• Integrate vector databases (Pinecone, Weaviate, FAISS or similar) into retrieval workflows—even if this is new territory, you'll learn fast.
• Instrument search pipelines with meaningful metrics: CTR, zero-result rate, latency—feeding the team's A/B experimentation loop.

Own the Engineering Bar

• Champion CI/CD, observability, testing, and infrastructure-as-code as non-negotiables, not afterthoughts.
• Lead design sessions with Engineers and Architects; translate product requirements into clean, maintainable technical solutions.
• Participate in code reviews and knowledge-sharing—actively raising the team's collective skill level.

What you bring

Must-Haves

• Strong Python foundation: 4+ years of professional backend or full-stack engineering experience with a
• deep Python focus—async patterns, type annotations, testing, and production-grade service design.
• Cloud-native experience: Proven experience designing and deploying cloud-native applications (
• GCP strongly preferred; AWS or Azure considered).
• Hands-on experience building resilient microservices and RESTful/gRPC APIs.
• Solid understanding of containerization (Docker), orchestration (Kubernetes), and serverless paradigms.
• Strong grounding in SOLID design principles and software craftsmanship.
• Good communicator who thrives in cross-functional, agile teams alongside ML engineers, architects, and product owners.
• Comfort using AI tools to accelerate development throughput.

Strongly Preferred — Search & ML

You don't need all of these on day one—but the more you bring, the faster you'll contribute:

• Search systems: Experience with search platforms: Elasticsearch, OpenSearch, Solr, or Algolia—index management, query DSL, relevance tuning.
• Vector search: Familiarity with vector search concepts and tooling: embeddings, approximate nearest neighbor (ANN), FAISS, Pinecone, Weaviate, or similar.
• Exposure to ML/AI patterns: RAG pipelines, LLM integration, prompt engineering, or fine-tuning workflows.
• Experience with AI orchestration frameworks such as LangChain, LangGraph, or Google ADK.
• Infrastructure-as-code experience (Terraform, Pulumi) and mature CI/CD pipeline ownership.

Physical Demands

PHYSICAL DEMANDS:

Licenses & Certifications

LICENSES & CERTIFICATIONS: None required.

Supervisory Responsibility

SUPERVISORY RESPONSIBILITY: No Supervisory Responsibility

Budget Responsibility

BUDGET RESPONSIBILITY: No

Company Information

COMPANY INFORMATION: Motion Industries offers an excellent benefits package which includes options for healthcare coverage, 401(k), tuition reimbursement, vacation, sick, and holiday pay.

Disclaimer

DISCLAIMER: This job description illustrates the general nature and level of work performed by employees within this job classification. It is not intended to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and skills required. Management retains the right to add or modify duties at any time.

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