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, Entrata’s post-trained model, we are looking for a Senior Machine Learning Engineer to help drive the next generation of our applied AI capabilities for the multi-family industry.
You will play a central role in fine-tuning, serving, and deploying open-weights foundation models and domain-specific LLMs, engineering high-throughput ML pipelines that power intelligent automation for millions of residents and property managers worldwide.
Responsibilities
Fine-tune, adapt, and align open-weights foundation models for domain-specific property management use cases using Supervised Fine-Tuning (SFT), preference optimization (DPO/RLHF), and parameter-efficient methods (LoRA/QLoRA).
Build scalable data filtering, instruction-tuning curation, and synthetic data generation pipelines tailored to prepare high-quality datasets for open-model training and continuous alignment.
Optimize open-model inference, serving, quantization, and deployment using frameworks like vLLM, TensorRT-LLM, or SGLang to maximize GPU throughput, lower latency, and minimize operating costs for FORGE.
Develop agentic AI systems leveraging function-calling, reasoning, and context window capabilities to automate multi-step enterprise workflows across Entrata’s platform.
Build domain-specific evaluation frameworks and safety guardrails to measure task accuracy, hallucination rates, and reliability of fine-tuned models against proprietary benchmarks.
Explore and deploy specialized model variants to expand FORGE’s multimodal and automated workflows.
Partner with product, data, and software engineering teams to integrate self-hosted open models seamlessly into Entrata’s microservices and production APIs.
Establish best practices for model versioning, open-model artifact management, continuous evaluation, and post-deployment monitoring.
Minimum Qualifications
- 5+ years of software engineering or machine learning engineering experience.
- Hands-on experience fine-tuning, adapting, or deploying large language models, including parameter-efficient techniques such as LoRA and QoRA (QLoRA).
- 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.
- Willingness to travel to client sites as needed.
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.
This band covers the full salary range for the role. Your offer within this range will depend on factors like experience, skills, and internal equity.
Level - P4
Benefits:
Flexible and transparent culture with remote and hybrid work options, generous vacation time, and frequent company recharge days for work-life balance.
Comprehensive medical, dental, and vision coverage, including fertility benefits, available for eligible employees and their families.
HSA/FSA options and employer-paid disability benefits provided for eligible employees.
Access to 401(k) or similar retirement plans with employer matching for eligible employees, ensuring long-term financial security.
Wellness initiatives promoting physical and mental well-being, access to an onsite gym at HQ, gym memberships, mental health resources, wellness challenges, and employee assistance programs.
Entrata Cares programs offers opportunities for volunteerism, charity events, and giving back to our community.
Exclusive Previ cell phone plan and discounts on services or local business partnerships for additional employee benefits.
Bi-annual swag drops for employees
Currently, Entrata hires in Arizona, Idaho, Utah, Wyoming, Texas, North Carolina, Florida, Georgia, South Carolina, Ohio, Pennsylvania, and Illinois for Exempt roles and Arizona, Idaho, Utah, Wyoming, Texas, North Carolina, and Florida for Non-Exempt roles.
Entrata is dedicated to creating a workplace where a diverse and inclusive team thrives in an environment free from discrimination. We provide equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, protected veteran status, or any other applicable characteristics protected by law.
It’s a great place to work! Will you join us?
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
