Machine Learning Engineer II

Sorry, this job was removed at 08:17 p.m. (CST) on Monday, May 19, 2025
Chicago, IL
Hybrid
110K-135K Annually
Cloud • Real Estate • Software • PropTech
Help us revolutionize real estate services.
The Role
Summary:
The Machine Learning Engineer II role is part of the Technology Team, which is responsible for providing industry-leading machine learning-based tools or processes to the Company, which provide a competitive advantage and efficiency. You will work closely with cross-functional teams to build intelligent systems that solve real-world problems using machine learning, deep learning, and data science techniques.

What You'll Do:
·         Design, deploy, fine-tune, and evaluate large language models (LLMs); develop effective prompting strategies to optimize performance for various business use cases.
·         Improve data quality by cleaning the company’s data and sourcing information from new data sources.
·         Use machine learning/ deep learning to enhance and automate processes in Lessen proprietary tools.
·         Translate business problems into scalable AI/ML solutions, particularly using LLMs, in areas such as copilot systems, intelligent voice assistants, and work order processing optimization.
·         Collaborate cross-functionally with teams to develop, refine, and scale data-driven procedures and workflows.
·         Foster a positive team environment.
·         Ensure confidentiality and integrity of internal and external data.
·         Perform ad-hoc projects and other duties as assigned.

You Should Have:
·         Phd or Masters degree in Math, Physics, Statistics, Computer Science, or other related fields
·         Strong mathematical and statistical skills
·         Programming Languages: SQL, Python
·         Understanding of ETL tools and database architecture
·         Familiarity with pytorch, pandas and cloud platform like AWS, Azure and GCP
·         Prompt engineering experience
·         Experience using a machine learning framework e.g. scikit-learn, pytorch or similar
·         Experience with a statistical software (e.g. R, SAS)
·         1-3 years of experience as a data scientist, working closely within a business
·         Experience with natural language processing
·         Advanced knowledge of Data Warehousing and BI best practices
·         Experience with big data tools such as Spark, Hadoop, etc.
·         Experience with Tableau or Superset

Compensation:
$110,000 - 135,000.00 annually
Pay is determined by several compensable factors, such as qualifications, skill level, competencies, and work location. 

What the Team is Saying

Jay Payne
Kirby Pumper
Maya Shea
Jay McKee
Jennifer Gordon
Trevon
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The Company
HQ: Scottsdale, Arizona
713 Employees
Year Founded: 1999

What We Do

Lessen is the tech-enabled, end-to-end property service provider that is transforming how commercial and residential real estate services are delivered and managed at scale. Lessen’s technology platform provides data-driven insights that unlock key growth opportunities for the entire real estate ecosystem—including investors, owners, managers, and service providers. The company leverages a network of over 30,000 vetted, qualified vendors (Lessen Affiliates) serving clients with over 1 million properties and completing more than 3.5 million work orders annually across an expanding range of services. Lessen, LLC is a venture-backed, privately held company with offices in Scottsdale and Chicago. To learn more, visit Lessen.com.

Why Work With Us

We make caring for and improving properties simpler, faster, better. Powered by tech and perfected by people, we deliver best-in-class, transformational solutions to deliver assets to market faster, keep businesses up and running, and improve customer and resident experiences. We're property services, simplified.

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About our Teams

Lessen LLC Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

At Lessen, managers decide how teams work best—office, home, or hybrid. We value flexibility, connection, and outcomes, investing in tools that keep everyone aligned and focused on delivering great results together.

Typical time on-site: 3 days a week
HQScottsdale, AZ
Chicago, IL
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