Principal Machine Learning Engineer

ProsperOps is the category leader in autonomous cloud cost optimization, founded by the leaders behind Rackspace's AWS Managed Services Business. We use sophisticated algorithms, AI, and automation to generate world class savings outcomes for AWS, Azure, and Google Cloud, while minimizing our customers' risk. We have over $5 billion dollars of cloud spend under management and serve sophisticated teams like Coinbase, Canva, SeatGeek, and TD Synnex. The cloud is incredibly powerful, but operating it cost effectively is complicated and time-consuming. Our mission is to remove complexity and deliver savings outcomes so every business can prosper in the cloud. We're a fully remote team, so 100% of our roles are open to applicants anywhere in the region in which the role is advertised.

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. 

ProsperOps, a Flexera company, is proud to be an equal opportunity employer.  Qualified applicants will be considered for open roles regardless of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by local/national laws, policies and/or regulations.

ProsperOps understands the value that results from employing a diverse, equitable, and inclusive workforce. We recognize that equity necessitates acknowledging past exclusion and that inclusion requires intentional effort. Our DEI (Diversity, Equity, and Inclusion) council is the driving force behind our commitment to championing policies and practices that foster a welcoming environment for all.

We encourage candidates requiring accommodations to please let us know by emailing [email protected].