Senior Machine Learning Engineer

Build and productionize machine learning and statistical models powering VuNet's observability platform for large-scale, continuous time-series and operational data.

Develop and optimize adaptive anomaly detection, forecasting, root cause analysis, and incident intelligence algorithms with measurable impact on product performance.

Engineer ML platform components for model lifecycle management, including versioning, experimentation, validation, safe rollout, and performance monitoring at scale.

Strong software engineering skills in Python.

Solid foundation in probability, statistics, statistical inference, machine learning, and time-series analysis.

Experience building or materially adapting ML/statistical algorithms and taking them from experimentation into reliable production systems.

Work Experience Required: Not explicitly mentioned in the JD.

Experienced in large-scale ML/Statistical algorithm design and production deployment in real-world, noisy, high-volume data environments.

Ability to independently identify impactful problems, reason from first principles, and drive solutions end-to-end with high ownership and agency.

Comfortable designing ML systems for distributed, streaming, low-latency, scalable environments involving observability, monitoring, or operational telemetry data.