Staff ML Engineer: AI Observability & Scale

FDE Times; New York (NY); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with match

Paid parental leave

Tuition reimbursement

Flexible PTO

Job summary

CoreWeave is building the AI-first cloud platform. We seek a Staff Machine Learning Engineer to lead ML systems powering anomaly detection, signal correlation, and incident understanding across observability and cloud services.

You will frame problems, build models, design evaluations, and deploy data and inference services at scale, partnering with engineers, PMs, researchers, and domain experts to deliver reliable, customer-facing capabilities.

Qualifications

• Significant experience designing and shipping production ML systems.
• Strong Python software engineering; Go or systems language a plus.
• Deep ML fundamentals: model selection, features, evaluation, failure analysis.
• Experience with time-series, logs, metrics, traces at scale.
• Ability to define evaluation methodology for complex ML problems.
• Excellent collaboration across research, product, and infra teams.

Responsibilities

• Lead design and delivery of production ML systems for observability.
• Develop anomaly detection, event correlation, ranking, and inference.
• Build evaluation datasets and frameworks for accuracy and safety.
• Translate research into scalable, maintainable services.
• Design data pipelines, feature gen, model serving, feedback loops.
• Integrate ML with telemetry platforms and customer experiences.
• Establish experiments, monitoring, reproducibility, and lifecycle practices.
• Mentor engineers and influence roadmaps across teams.

Skills

Python

Go

Systems thinking

Time-series data

Observability

Machine learning fundamentals

Communication

Mentorship

Tools

Grafana

Prometheus

VictoriaMetrics

ClickHouse

Loki

Kafka

Kubernetes

Job description

CoreWeave is building the AI-first cloud platform. We seek a Staff Machine Learning Engineer to lead ML systems powering anomaly detection, signal correlation, and incident understanding across observability and cloud services.

You will frame problems, build models, design evaluations, and deploy data and inference services at scale, partnering with engineers, PMs, researchers, and domain experts to deliver reliable, customer-facing capabilities.