Principal Machine Learning Engineer

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🕒 May 19

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ProsperOps

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2018

☁️ SaaS

🤝 B2B

🏢 Enterprise

💰 $72M Series A - ProsperOps on 2023-02

SaaS • B2B • Enterprise

ProsperOps is a SaaS company that provides autonomous FinOps automation to optimize cloud costs across AWS, Google Cloud, and Microsoft Azure. It combines AI-enabled rate optimization (Autonomous Discount Management) with resource scheduling and workload optimization (ProsperOps Scheduler) to maximize savings, minimize commitment lock-in risk, and reduce wasted spend. The platform passively ingests cloud billing data, continuously calculates and executes optimal commitment and scheduling adjustments, and delivers reporting, benchmarking, and showback for FinOps and DevOps teams.

📋 Description

• 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.

🏖️ Benefits

• Flexible work arrangements • Professional development opportunities