Machine Learning Engineer II

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.

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.

This is a hybrid position, Tuesday and Thursday in the office.

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:

Minimum Qualifications

• PhD or Master’s degree in Math, Physics, Statistics, Computer Science, or other related fields

• 1-3 years of experience as a data scientist, working closely within a business

• 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)

• 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

These are the professional skills we would expect from an individual fully established in this role.

• Verbal Communication – Proficient

• Written Communication – Proficient

• Teamwork – Advanced

• Relationships – Advanced

• Organizational Awareness – Advanced

• Learning Agility – Advanced

• Analysis – Advanced

• Problem Solving – Advanced

• Process Orientation – Advanced

• Prioritization – Advanced

• Customer Service – Proficient

• Process Orientation – Advanced

• Negotiation - Advanced

Why Lessen:

· Competitive compensation

· Health, Dental, Vision, Life, Disability options

· 401K retirement savings plan

· Paid vacation, federal and floating holidays

· Maternity/Paternity Pay

· Career advancement opportunities

· All the tools you'll need to be successful

Lessen is intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. We’re looking for teammates that are enthusiastic, empathetic, curious, motivated, reliable, and will help us amplify the positive & inclusive culture we’ve been building. Lessen is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.