ML Search Engineer

Posted Yesterday
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Birmingham, AL, USA
In-Office
Senior level
Automotive • Hardware • Logistics
The Role
Build and operate production ML-powered product search systems using Python, React, cloud-native GCP services, retrieval and ranking pipelines, APIs, Elasticsearch, and vector databases. Develop ML inference, embedding, transformer, LLM, and reranking workflows; create responsive frontend interfaces; and own testing, observability, CI/CD, infrastructure, deployment, monitoring, and on-call responsibilities. Collaborate with architects and product teams, improve search relevance through experimentation, and mentor junior and mid-level engineers.
Summary Generated by Built In

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 Full Stack Engineer on the ML/AI Search team, you'll design and build both the frontend and backend systems that power product discovery for millions of industrial buyers—from scalable retrieval pipelines, APIs, and Frontend 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 and React 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 

  • Drive frontend architecture decisions, establishing development standards, and creating reusable component libraries. 

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. 

  • Build clean, responsive, and production-ready interfaces from wireframes or Figma designs. 

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 and React foundation: 6+ years of professional backend or full-stack engineering experience with a deep Python/React (e.g., Next.js, Vite.js, Remix.js, Gatsby.js) focus—async patterns, type annotations, testing, and production-grade service/component design. 

  • Cloud-native experience: Proven experience designing and deploying cloud-native applications ( 

GCP strongly preferred; AWS or Azure considered). 

  • Hands-on experience building resilient high throughput 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. 

  • Strong experience of using and managing Monorepos 

  • Strong understanding of relational (e.g., PostgreSQL, MySQL, Oracle) and non-relational databases (e.g., MongoDB, DynamoDB). 

  • Mentorship: Provide guidance and technical knowledge sharing to mid-level and junior developers.  

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, OpenTofu) and mature CI/CD pipeline ownership. 

WHO YOU ARE 

Fearless Builder 

A working proof-of-concept beats a thousand slide decks. Speed and quality are both non-negotiable. 

 

Relentless Learner 

You pick up new technologies fast and have a genuine eagerness to master whatever comes next. 

Architecture-Minded 

You design scalable, fault-tolerant services as second nature and aren't afraid to challenge the status quo. 

 

Ownership-Driven 

Code isn't done until it's tested, documented, and monitored. Your name on a release means something. 

Search-Curious 

You may not have built a search system yet—but you're excited by the challenge and ready to go deep. 

 

Team Multiplier 

You give and welcome candid feedback and actively make the people around you better. 

PHYSICAL DEMANDS:

LICENSES & CERTIFICATIONS: None required.

SUPERVISORY RESPONSIBILITY: No Supervisory Responsibility

BUDGET RESPONSIBILITY: No

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: 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.

Not the right fit?  Let us know you're interested in a future opportunity by joining our Talent Community on jobs.genpt.com or create an account to set up email alerts as new job postings become available that meet your interest!

GPC conducts its business without regard to sex, race, creed, color, religion, marital status, national origin, citizenship status, age, pregnancy, sexual orientation, gender identity or expression, genetic information, disability, military status, status as a veteran, or any other protected characteristic. GPC's policy is to recruit, hire, train, promote, assign, transfer and terminate employees based on their own ability, achievement, experience and conduct and other legitimate business reasons.

Skills Required

  • At least 6 years of professional backend or full-stack engineering experience with a strong Python and React focus
  • Experience with async patterns, type annotations, testing, and production-grade service and component design
  • Experience designing and deploying cloud-native applications; GCP preferred, with AWS or Azure accepted
  • Hands-on experience building resilient, high-throughput microservices and RESTful or gRPC APIs
  • Understanding of Docker, Kubernetes, and serverless architectures
  • Knowledge of SOLID design principles and software craftsmanship
  • Strong communication skills and ability to work cross-functionally in agile teams
  • Comfort using AI tools to accelerate development
  • Experience using and managing monorepos
  • Understanding of relational databases such as PostgreSQL, MySQL, or Oracle
  • Understanding of non-relational databases such as MongoDB or DynamoDB
  • Ability to mentor mid-level and junior developers
  • Experience with search platforms such as Elasticsearch, OpenSearch, Solr, or Algolia
  • Familiarity with vector search, embeddings, approximate nearest neighbor search, FAISS, Pinecone, or Weaviate
  • Exposure to RAG pipelines, LLM integration, prompt engineering, or fine-tuning workflows
  • Experience with LangChain, LangGraph, or Google ADK
  • Infrastructure-as-code experience with Terraform, Pulumi, or OpenTofu
  • Mature CI/CD pipeline ownership experience

Genuine Parts Company Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Genuine Parts Company and has not been reviewed or approved by Genuine Parts Company.

  • Retirement Support — Retirement programs include a 401(k) with company match and an Employee Stock Purchase Plan, with profit sharing and pension plans also mentioned. These elements indicate strong long-term financial support alongside ownership opportunities.
  • Healthcare Strength — Benefits encompass medical, dental, and vision coverage with HSA and FSA options plus income-protection coverages like life, AD&D, and disability. This breadth suggests a robust core health and protection offering.
  • Parental & Family Support — Paid maternity and paternity leave are provided in addition to short‑term disability, and an Employee Assistance Program supports families with counseling and life tools. These programs reinforce family support alongside standard PTO.

Genuine Parts Company Insights

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The Company
HQ: Atlanta, GA
4,400 Employees
Year Founded: 1928

What We Do

Genuine Parts Company (GPC), founded in 1928, is a global service organization engaged in the distribution of automotive and industrial replacement parts. We serve hundreds of thousands of customers from a network of more than 10,000 locations in 14 countries and have approximately 50,000 employees.

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