What are the responsibilities and job description for the Senior AI/ML Engineer position at Wizerr AI?
We are hiring a Senior AI/ML Engineer at Wizerr.
About Wizerr
Wizerr is the intelligence layer for AI infrastructure hardware - the components and systems that go into AI factories and AI devices. The trillion-dollar AI buildout runs on physical components — power, memory, optics, signal integrity.
Wizerr ELX is our component intelligence graph that works at the intersection of large-scale structured data, LLMs, and a real domain ontology — and we ship to
paying customers every week.
The Role
You'll own a meaningful slice of our data, ML, and applied AI surface — working directly with the lead technologist on the systems that power the product. The pipelines that ingest and structure component data. The LLM-driven reasoning customers actually pay for.
Hands-on, production-focused. Concept to deployment to keeping it healthy at 3am. Strong ownership, minimal hand-holding.
What You'll Do
- Own data and ML pipelines. Ingest, clean, and structure domain data from messy, heterogeneous sources. Build the pipelines everything else runs on.
- Build applied AI features. Retrieval, structured extraction from technical documents, agentic reasoning over the graph — backed by real evaluation, not vibes.
- Improve search and ranking. Iterate on the matching, scoring, and ranking logic that decides what customers see.
- Ship to production. APIs customers and internal teams can call — with the reliability, observability, and evaluation that implies.
- Run it on cloud. AWS and/or GCP. Pick up new services when the problem calls for it.
- Cross-stack when needed. Drop into backend or frontend to ship a feature end-to-end.
What We're Looking For
- 5 years ML or data engineering, with hands-on production LLM work in the last 1–2 years.
- Strong Python and SQL. Comfort designing for performance on large, evolving datasets.
- Deployed and operated real workloads on AWS and/or GCP.
- A track record of owning things end-to-end — not notebooks, demos, or handoffs.
- Comfort with messy, domain-shaped data.
- Clear written communication. We're async-first; you'll document your thinking and drive your own work.
Nice to Have
- Background in electronics, EE, semiconductors, or another deep technical domain.
- Parametric / faceted search, product catalogs, or structured retrieval at scale.
- Designed evaluation frameworks for LLM pipelines.
- Exposed internal tools as agent-callable APIs.
How We Work
Small, senior team. Fully remote, async-first, global. We use AI tooling aggressively in our own workflow and ship into production every week.
How to Apply
Email shine@wizerr.ai with your resume or LinkedIn, and a short note about an AI or ML pipeline you've actually shipped — what you owned, and what you learned.