Senior Machine Learning Engineer – LLM & ML Systems
Confirmed live in the last 24 hours
SolarWinds
Job Description
At SolarWinds, we’re a people-first company. Our purpose is to enrich the lives of the people we serve—including our employees, customers, shareholders, partners, and communities. Join us in our mission to help customers accelerate business transformation with simple, powerful, and secure solutions.
The ideal candidate thrives in an innovative, fast-paced environment and is collaborative, accountable, ready, and empathetic. We’re looking for individuals who believe they can accomplish more as a team and create lasting growth for themselves and others. We hire based on attitude, competency, and commitment. Solarians are ready to advance our world-class solutions in a fast-paced environment and accept the challenge to lead with purpose. If you’re looking to build your career with an exceptional team, you’ve come to the right place. Join SolarWinds and grow with us!
We are looking for a Senior Machine Learning Engineer to join our Platform Machine Learning team in Bangalore. In this role, you will design and build production-grade machine learning systems that power intelligent capabilities across the SolarWinds observability platform.
This position focuses on building reliable ML systems and LLM-powered services, including model pipelines, scalable inference systems, and modern MLOps workflows. You will work closely with platform engineers, product managers, and other ML engineers to deliver ML-driven features that operate reliably in real-world production environments.
Responsibilities:
- Design, build, and deploy machine learning systems that process large-scale telemetry and operational data.
- Develop and maintain end-to-end ML pipelines, including data preparation, feature engineering, model training, evaluation, and production deployment.
- Build and integrate LLM-powered capabilities, such as Retrieval-Augmented Generation (RAG) pipelines and intelligent automation features.
- Implement and maintain MLOps best practices, including experiment tracking, model monitoring, reproducibility, and automated training and deployment workflows.
- Collaborate closely with platform, infrastructure, and product teams to integrate ML capabilities into distributed SaaS systems.
- Contribute to improving platform reliability and automation through ML-driven insights and predictive systems.
- Evaluate and integrate modern ML tools and techniques that can enhance observability and platform intelligence.
- Support a culture of strong engineering practices including code quality, documentation, and collaborative development.
Must Have
- 5+ years of experience in machine learning engineering or software engineering.
- Strong programming experience in Python.
- Hands-on experience with machine learning f
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