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 environments—from on-premises to SaaS to containers to cloud.

We’re transforming the software industry.  We’re Flexera.  With more than 50,000 customers across the world, we’re achieving that goal. But we know we can’t 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 why we’re consistently recognized by Gartner, Forrester and IDC as a category leader in the marketplace. Learn more at flexera.com

We are seeking a Principal Machine Learning Engineer with 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 a high-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:

Build end-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 of MLOps best practices and champion operational excellence for ML infrastructure.
Build and deploy models for cloud 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 delivering ML projects into production at scale, preferably in a SaaS/cloud infrastructure setting.
Strong hands-on experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and Python.

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