Senior Machine Learning Engineer
@ EntrataSenior Machine Learning Engineer
This job is still taking applications, but it's been up a while.
About the job
Entrata is a global leader in AI-driven property management tech, providing intelligent leasing, payment, and communication tools. We focus on AI development, innovation, and creating a diverse, transparent workplace. Join us to shape the future of AI in property management.
Requirements
- 5-10 years software development
- 1-2 years operational experience
- 3+ years AI solution experience
- Proficient in Python
- Strong AWS experience
Qualifications
- Bachelor’s in computer science
- Experience with infrastructure as code
- AI components in production
Full job description
We are seeking a Senior Machine Learning Engineer to help build and scale Entrata’s applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management use cases, building reliable model training and evaluation pipelines, and deploying AI systems into production.
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.
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