Machine Learning Engineer

Job not on LinkedIn

🕒 July 27

🐊 Florida – Remote

🐊 Florida – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Roper Technologies, Inc.

WebsiteLinkedInAll Job Openings

10,000+ employees

☁️ SaaS

🤝 B2B

🏭 Manufacturing

💰 $2G Post-IPO Debt - Roper Technologies on 2025-08

SaaS • B2B • Manufacturing

Roper Technologies, Inc. is a diversified technology company that acquires, develops, and operates niche, mission‑critical software and technology‑enabled product businesses. Its public disclosures list operating segments such as Application Software, Network Software, and Technology Enabled Products, indicating a portfolio of specialized software (including SaaS-like application businesses) and engineered hardware sold mainly to other businesses and industries.

📋 Description

• Design, build, and deploy machine learning models and AI systems in production environments • Develop components such as Model inference services, Data and feature pipelines, Complex recommendation and matching services, Vision based analysis systems, Evaluation and monitoring pipelines • Optimize models for performance, reliability, and cost efficiency • Build systems that integrate with enterprise tools and APIs • Write high-quality, maintainable, and well-tested code • Participate in architecture design and technical reviews • Partner with product, data engineering, and infrastructure teams • Help identify high-impact AI use cases within portfolio companies

🎯 Requirements

• 3+ years of experience in software engineering, data science, or machine learning (more for senior roles) • Experience building and deploying production software systems • Strong programming skills in Python (experience in additional languages is a plus) • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) • Understanding of modern AI architectures, including LLM-based systems • Experience working with cloud environments (AWS, Azure, or GCP)

🏖️ Benefits

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development