Principal Machine Learning Engineer

Flexera saves customers billions of dollars in wasted technology spend. A pioneer in Hybrid ITAM and FinOps Flexera provides award-winning data-oriented SaaS solutions for technology value optimization (TVO) enabling IT finance procurement and cloud teams to gain deep insights into cost optimization compliance and risks for each business service. Flexera One solutions are built on a set of definitive customer supplier and industry data powered by our Technology Intelligence Platform that enables organizations to visualize their Enterprise Technology Blueprint in hybrid environmentsfrom on-premises to SaaS to containers to cloud.

Were transforming the software industry. Were Flexera. Withmore than 50000 customersacross the world were achievingthat goal.Butwe knowwe cant do any of that without our team.Ready to help us re-imagine the industry during a time of substantial growth and ambitious plans Come and see whywere consistently recognized by Gartner Forrester and IDCas a category leader in the marketplace.Learn more at

We are seeking aPrincipalMachine Learning Engineerwith a strong technical foundation and proven technical leadership experience to drive the development and deployment of ML and GenAI-powered solutions in a cloud-native environment.

In this role you will work with ahigh-impact team of AI/ML Data and MLOps engineers in a matrixed org structure collaborate cross-functionally with engineering product and DevOps and own strategic initiatives focused on intelligent workload management cloud cost optimization and infrastructure automation.

If you are passionate about building scalable ML systems driving team performance and bringing cutting-edge AI (including LLMs and Agentic AI) into production this is your opportunity to make a meaningful impact.

Key Responsibilities:

Buildend-to-end AI/ML/Agentic-AI solution from ideation research and experimentation to deployment and monitoring in production.
Manage project timelines deliverables and cross-team dependencies in coordination with product and engineering leads.
Translate business and technical requirements into ML roadmap architecture and actionable workstreams.
Drive adoption ofMLOps best practices and champion operational excellence for ML infrastructure.
Build and deploy models forcloud workload prediction resource optimization and intelligent automation.
Integrate GenAI LLM-based and Agentic AI solutions into customer-facing products and internal systems.
Communicate ML strategy progress and insights effectively to both technical and non-technical stakeholders.

Requirements:

BTech/BE Masters or Ph.D. in Computer Science Machine Learning AI or a related field.
10 years of experience in ML/AI/DE
Proven track record of deliveringML projects into production at scale preferably in a SaaS/cloud infrastructure setting.
Strong hands-on experience withML frameworks (-learn TensorFlow PyTorch) andPython.

Should have experience with AWS Terraform. Prior work experience with Databricks and Spark is preferred.
Hands-on experience withGenAI LLMs and Agentic AI frameworks (e.g. OpenAI Hugging Face LangChain) including practical implementation in production.