Senior Machine Learning Engineer, AI Insights
$165k - $242k • 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 Senior Machine Learning Engineer to join the AI Insights team. This role focuses on building customer-facing AI capabilities that leverage machine learning, observability, and production software engineering. You will develop ML systems, services, evaluation frameworks, and product capabilities to enable reliable AI-powered troubleshooting and optimization in real-world environments. The position involves working across the full ML development lifecycle, from problem understanding and data preparation to model development, integration, and performance improvement based on feedback. You will collaborate with cross-functional teams to transform complex problems into robust systems and will have significant ownership of production components while influencing the team's technical direction.
Responsibilities
- Build and deploy 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 on high-volume telemetry.
- Create datasets, experiments, and evaluation frameworks to assess model quality, robustness, usefulness, and failure modes.
- Build data pipelines, feature-generation workflows, inference services, and feedback loops for continuous improvement.
- Integrate ML capabilities with telemetry platforms and customer-facing experiences.
- Collaborate with engineers on metrics, logs, traces, telemetry enrichment, platform APIs, and data infrastructure.
- Monitor and enhance the quality, latency, reliability, and cost of ML-powered services in production.
- Investigate data and model failures, identify root causes, and implement durable fixes.
- Make informed trade-offs across model quality, interpretability, operational complexity, latency, and cost.
- Contribute to technical designs, code reviews, testing standards, and operational practices.
- Partner with technical leaders to break down complex initiatives and deliver incrementally.
- Share knowledge through documentation, mentorship, and collaboration.
Requirements
- 5+ years of experience designing and shipping production machine learning systems.
- Bachelor’s degree in Computer Science, Computer Engineering, Information Technology, or a related technical field.
- Strong software engineering skills in Python; experience with Go or another systems-oriented language is a plus.
- Solid 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.
- Experience building reliable data and inference services, not just notebooks or offline prototypes.
- Experience defining and implementing evaluation methodology for ambiguous or domain-specific ML problems.
- Strong debugging and systems-thinking skills, including reasoning about data quality, distributed systems, latency, and operational failure modes.
- Experience taking an ML capability from hypothesis through production launch and iteration.
- Excellent communication and collaboration skills, with the ability to work effectively across engineering, research, product, and infrastructure teams.
- A track record of owning complex technical work and delivering results.