Description review
AI Infrastructure / Product Engineer
Clera · remote · back to the listing
HR standards
71/100
solid
Title ↔ description
69/100
needs work
Reads as
Machine Learning Engineer
89% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
Large employers
- Applied AI Engineer Automattic
- Machine Learning Engineer, CX Intelligence Coinbase
- AI Engineer - FDE (Forward Deployed Engineer) Databricks
- AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector Databricks
- Senior AI Engineer – Notebooks Datadog
Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
- Member of Technical Staff (applied) Anthrogen
- Aptura AI | Full-Time | MTS (Applied AI), MTS (SWE / Product) | London | ONSITE / HYBRID Aptura AI
- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
- Staff AI Engineer - Agent Architecture & Behavior Artisan
What the listing never says
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
About the Role
As an AI Infrastructure / Product Engineer, you will work at the intersection of AI research and product development at a healthtech company building AI products. You will help turn experiments into dependable systems and features, and build ways to measure and improve their quality.
What You'll Do
• Build repeatable benchmarks and evaluation pipelines to measure model accuracy, hallucinations, retrieval quality, latency, and cost.
• Create dashboards that make changes in system performance visible to the team.
• Develop production retrieval, drafting, document, and agent workflows from research prototypes.
• Build backend services, APIs, and internal tools to help test and release improvements.
• Deploy and operate cloud infrastructure, including monitoring, databases, delivery pipelines, and reliable operations.
• Collaborate with AI research while staying connected to product and user needs.
What We're Looking For
• At least 3 years of experience as a software, infrastructure, or product engineer building and deploying production systems.
• Strong Python skills and hands-on cloud deployment experience.
• Experience with APIs, databases, backend services, deployment pipelines, and production monitoring.
• Experience building evaluation pipelines, benchmarks, or assessment systems for machine learning or AI systems.
• Ability to turn ambiguous ideas and experimental code into usable, maintainable products.
• Interest or experience in LLMs, retrieval-augmented generation, agents, AI benchmarks, or document automation.
• Full-stack experience is helpful. Familiarity with FastAPI, Docker, React, Next.js, Postgres, or vector databases is a plus.
Compensation & Benefits
Annual base salary is $180,000 to $260,000 USD, depending on skills, experience, and role scope. Visa sponsorship is not available.
Location
Remote within the United States.
As an AI Infrastructure / Product Engineer, you will work at the intersection of AI research and product development at a healthtech company building AI products. You will help turn experiments into dependable systems and features, and build ways to measure and improve their quality.
What You'll Do
• Build repeatable benchmarks and evaluation pipelines to measure model accuracy, hallucinations, retrieval quality, latency, and cost.
• Create dashboards that make changes in system performance visible to the team.
• Develop production retrieval, drafting, document, and agent workflows from research prototypes.
• Build backend services, APIs, and internal tools to help test and release improvements.
• Deploy and operate cloud infrastructure, including monitoring, databases, delivery pipelines, and reliable operations.
• Collaborate with AI research while staying connected to product and user needs.
What We're Looking For
• At least 3 years of experience as a software, infrastructure, or product engineer building and deploying production systems.
• Strong Python skills and hands-on cloud deployment experience.
• Experience with APIs, databases, backend services, deployment pipelines, and production monitoring.
• Experience building evaluation pipelines, benchmarks, or assessment systems for machine learning or AI systems.
• Ability to turn ambiguous ideas and experimental code into usable, maintainable products.
• Interest or experience in LLMs, retrieval-augmented generation, agents, AI benchmarks, or document automation.
• Full-stack experience is helpful. Familiarity with FastAPI, Docker, React, Next.js, Postgres, or vector databases is a plus.
Compensation & Benefits
Annual base salary is $180,000 to $260,000 USD, depending on skills, experience, and role scope. Visa sponsorship is not available.
Location
Remote within the United States.