Staff Machine Learning Engineer, AI Insights
$180k - $250k • Remote • New York, NY
Posted 5d ago
Job Location
New York, NY
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
CoreWeave is seeking a Staff Machine Learning Engineer to join the AI Insights team. This role will be a technical leader responsible for defining and implementing machine learning systems that power anomaly detection, signal correlation, incident understanding, recommendations, and other intelligence capabilities across CoreWeave’s observability and cloud platforms. You will work across the full machine learning lifecycle, from problem framing and model development to evaluation, service building, and scaled operation. The position involves close collaboration with software engineers, product managers, researchers, and domain experts to transform innovative ideas into reliable customer experiences, focusing on building underlying ML systems for AI-powered troubleshooting and optimization in real-world environments.
Responsibilities
- Lead the technical design and delivery of production machine learning systems for infrastructure observability, troubleshooting, and optimization.
- Develop approaches for anomaly detection, time-series analysis, event correlation, ranking, recommendation, classification, and root-cause inference across high-volume telemetry.
- Build evaluation frameworks and datasets to measure accuracy, usefulness, robustness, and safety in operational scenarios.
- Translate research and prototypes into maintainable, scalable services with clear operational ownership.
- Design data pipelines, feature-generation workflows, model-serving paths, and feedback loops for continuous improvement.
- Integrate ML capabilities with telemetry platforms and customer-facing experiences.
- Establish practical standards for experimentation, offline and online evaluation, monitoring, reproducibility, and model lifecycle management.
- Make thoughtful trade-offs across model quality, latency, cost, interpretability, reliability, and ease of operation.
- Work with teams responsible for telemetry and platform APIs to create coherent cross-system intelligence.
- Mentor engineers and raise the technical bar for machine learning and production engineering.
- Communicate technical decisions clearly and influence roadmaps across teams.
Requirements
- Significant experience designing and shipping production machine learning systems.
- Strong software engineering skills in Python.
- Deep understanding of machine learning fundamentals, including model selection, feature engineering, experimentation, evaluation, and failure analysis.
- Experience working with time-series, event, log, metric, trace, or other operational data at scale.
- Demonstrated ability to define evaluation methodology for ambiguous or domain-specific ML problems.
- Strong systems thinking and ability to reason about distributed systems, data quality, latency, observability, and operational failure modes.
- Excellent communication and collaboration skills.
- Track record of technical leadership, mentorship, and influence.