Description review
Member of Technical Staff, Agents
Clera · Remote - Palo Alto · back to the listing
HR standards
64/100
needs work
Title ↔ description
71/100
solid
Reads as
Machine Learning Engineer
98% 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
- 16 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- 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
Join a small, senior team building autonomous AI agents that handle real executive workflows. You will design new capabilities, measure their reliability, and improve them using evidence from real conversations before changes reach users.
What You'll Do
• Build agents that complete delegated work end to end with minimal user oversight.
• Define trustworthy measures of agent quality and evaluate performance across representative tasks.
• Develop new agent capabilities for tools people already use, and verify they are ready before launch.
• Investigate production failures and deliver durable, measurable fixes.
• Build systems to detect known failure patterns and less predictable issues at scale.
• Improve agent recovery when tools or websites fail.
• Create repeatable evaluation practices so engineers can assess whether agent changes improve outcomes.
What We're Looking For
• At least 3 years in data science or machine learning, building or delivering evaluation systems, metrics, or product quality measurement.
• Strong production proficiency in Python and SQL, including analysis of large datasets and automated pipelines.
• Experience designing evaluation frameworks with measurable criteria, representative datasets, and appropriate metrics.
• Experience building or operating agents for real users and improving their reliability.
• Familiarity with statistics, experiment design, and realistic end-to-end simulations.
• Experience owning systems through production launch and measuring their impact.
• Experience with post-training, fine-tuning, or reinforcement learning is relevant.
• Working knowledge of Django, React, and TypeScript is useful.
• Typically suited to candidates with fewer than 5 years of engineering experience and a track record of progression or startup ownership.
Compensation & Benefits
Base salary: $200,000 to $300,000 annually. Visa sponsorship is not available.
Location
On-site in Palo Alto, California, with four days per week in the office.
Join a small, senior team building autonomous AI agents that handle real executive workflows. You will design new capabilities, measure their reliability, and improve them using evidence from real conversations before changes reach users.
What You'll Do
• Build agents that complete delegated work end to end with minimal user oversight.
• Define trustworthy measures of agent quality and evaluate performance across representative tasks.
• Develop new agent capabilities for tools people already use, and verify they are ready before launch.
• Investigate production failures and deliver durable, measurable fixes.
• Build systems to detect known failure patterns and less predictable issues at scale.
• Improve agent recovery when tools or websites fail.
• Create repeatable evaluation practices so engineers can assess whether agent changes improve outcomes.
What We're Looking For
• At least 3 years in data science or machine learning, building or delivering evaluation systems, metrics, or product quality measurement.
• Strong production proficiency in Python and SQL, including analysis of large datasets and automated pipelines.
• Experience designing evaluation frameworks with measurable criteria, representative datasets, and appropriate metrics.
• Experience building or operating agents for real users and improving their reliability.
• Familiarity with statistics, experiment design, and realistic end-to-end simulations.
• Experience owning systems through production launch and measuring their impact.
• Experience with post-training, fine-tuning, or reinforcement learning is relevant.
• Working knowledge of Django, React, and TypeScript is useful.
• Typically suited to candidates with fewer than 5 years of engineering experience and a track record of progression or startup ownership.
Compensation & Benefits
Base salary: $200,000 to $300,000 annually. Visa sponsorship is not available.
Location
On-site in Palo Alto, California, with four days per week in the office.