Senior Machine Learning Engineer

Job description

Since 2003, Entrata has evolved from a visionary, student-led startup into a global leader in AI-driven property management technology. Today, we power the industry's most essential operating system, serving owners and residents worldwide through a comprehensive suite of intelligent leasing, payment, and communication tools powered by cutting-edge AI. With a proven track record of sustained growth and a global team of more than 2,200 employees, we offer the rare combination of established stability and high-velocity innovation. Recognized by the Silicon Slopes Hall of Fame and the Utah Business Fast 50, Entrata fosters a culture of radical transparency and entrepreneurial energy. At Entrata, we create an environment where different perspectives are valued and respected. Those perspectives challenge assumptions, strengthen our decisions, and raise the bar as we reshape the global living experience through AI-powered solutions. Following the launch of [**Forge**](https://www.entrata.com/blog/introducing-forge-a-language-model-built-for-multifamily), Entrata’s proprietary AI platform, we are looking for a **Senior Machine Learning Engineer** to drive the next generation of our applied AI capabilities. You will play a central role in fine-tuning Forge, optimizing domain-specific foundation models, and engineering robust ML pipelines that power intelligent automation for millions of residents and property managers worldwide. ### Responsibilities - Fine-tune and adapt large language models for Entrata-specific use cases using supervised fine-tuning and other post-training techniques. - Build scalable data preparation, curation, filtering, and synthetic data pipelines to support model training and evaluation. - Develop agentic AI systems that can reason across multi-step workflows, use tools, retrieve context, and operate reliably in production. - Build evaluation frameworks and benchmarks to measure model quality, safety, reliability, and task performance. - Optimize model inference, serving, and deployment for performance, cost, and scalability. - Partner with engineering, product, and data teams to integrate AI capabilities into Entrata products and workflows. - Help establish best practices for model experimentation, fine-tuning, evaluation, and deployment. ### Minimum Qualifications - 5+ years of software engineering or machine learning engineering experience. - Hands-on experience fine-tuning, adapting, or deploying large language models. - Strong proficiency with Python and PyTorch or similar deep learning frameworks. - Experience building ML data pipelines, training workflows, and evaluation systems. - Experience deploying machine learning models into production environments. - Familiarity with modern LLM tooling, model serving, and inference frameworks. - Strong understanding of machine learning fundamentals and model performance tradeoffs. ### Preferred Qualifications - Experience with supervised fine-tuning, preference optimization, or related post-training techniques. - Experience building agentic systems, tool-using models, or retrieval-based AI applications. - Experience with distributed training or GPU-based model workloads. - Familiarity with frameworks such as vLLM, DeepSpeed, FSDP, or similar technologies. - Experience working with enterprise or domain-specific AI applications. - Bachelor’s or advanced degree in Computer Science, Machine Learning, Engineering, or a related field, or equivalent practical experience.