ML Search Engineer

DEPLOY has been retained by a leading industrial parts distributor for an on site role in Birmingham Alabama. We are looking for an ML Search Engineer (Software Engineer III)

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

ABOUT THE ROLE

Were 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 youll design and build both the frontend and backend systems that power product discovery for millions of industrial buyersfrom scalable retrieval pipelines APIs and Frontend interfaces that make AI accessible.

This isnt a research role. Youll 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 foundationif you also bring experience in search systems vector databases or Elasticsearch youll hit the ground running from day one.

WHAT YOULL DO

Build & Ship Search and AI-Powered Systems

• Design develop and deploy production Python services end-to-endfrom 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 servicesCloud 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 workflowseven if this is new territory youll learn fast.

• Instrument search pipelines with meaningful metrics: CTR zero-result rate latencyfeeding the teams 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-sharingactively raising the teams 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. ) focusasync 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 dont need all of these on day onebut the more you bring the faster youll contribute:

• Search systems: Experience with search platforms:

Elasticsearch OpenSearch Solr or Algoliaindex 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 arent afraid to challenge the status quo.

Ownership-Driven

Code isnt done until its tested documented and monitored. Your name on a release means something.

Search-Curious

You may not have built a search system yetbut youre 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.