Join Datadog as a Staff Applied Scientist to lead the evaluation strategy for AI-driven Dashboards in a hybrid work environment.
Posted by employer 4 months ago
First seen on Joblaze 4 months ago
Last verified on the company career page 16 hours ago
Skills & Technologies
AI in the day-to-day
We are transforming Dashboards into an AI-native control surface.
Requirements
Not disclosed in this posting: visa sponsorship.
Benefits
Joblaze summary
In the role of Staff Applied Scientist for Dashboards at Datadog, the individual will focus on developing and implementing evaluation strategies for the AI-driven dashboard system, ensuring high-quality metrics and tool-selection accuracy. Key skills include a strong background in machine learning and experience in measuring ML systems at scale, alongside technical leadership capabilities. This position is ideal for seasoned professionals with over a decade of experience in applied science or engineering, particularly those who thrive in ambiguous environments and can drive cross-functional initiatives.
Joblaze insights
Quick facts
From the original posting
The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces—a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action – providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas.
We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number — it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success.
The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user’s query can result in the agent making decisions against dozens of visualizations and data sources – both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us.
What You’ll Do:
Who You Are:
Benefits and Growth:
#LI-Hybrid
Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.
About Datadog:
Standard company text repeated across Datadog's postings is omitted here.