Senior Machine Learning Engineer (Homes.com)

Job Description

OVERVIEW 

CoStar Group (NASDAQ: CSGP) is a leading global provider of commercial and residential real estate information, analytics, and online marketplaces.  Included in the S&P 500 Index and the NASDAQ 100, CoStar Group is on a mission to digitize the world’s real estate, empowering all people to discover properties, insights and connections that improve their businesses and lives.  

 

Homes.com is already one of the fastest growing real estate portals in the industry, we are driven to be #1. Just ask Brad Bellflower, Chief Change Officer at Apartments.com. After its acquisition in 2014, Apartments.com quickly turned into the most popular place to find a place. Proven success at the highest level – and we’re doing it again with the new Homes.com.  Homes.com is a CoStar Group company with 20+ years' experience in leading and growing digital marketplaces. We pride ourselves on continually improving, innovating, and setting the standard for property search and marketing experiences. With Homes.com we’re building a brand on the cusp of defining the industry. 

We’re looking for big thinkers, brave leaders, and creative advertising wizards ready to influence a new age of homebuying within a tried-and-true, award-winning company.  

Learn more about Homes.com.  

 

CoStar delivers real-time, verified real estate data that helps clients confidently spot great opportunities and make smart choices ahead of competitors. By combining the power of CoStar’s independent research organization – the industry’s largest – with global data delivery, software, and application solutions, clients can act on opportunities with confidence. 

 

Machine Learning Engineers at CoStar play an important role in this process, by mining data from sources including billions of pageviews, millions of images, vast geographic data, deep property content, and much more. We enhance our extensive property database, personalize our customers’ experience on our product websites, and create innovative datasets and forecasts that are the industry standards in our market leading products. 

 

We are looking for a Machine Learning Engineer to join our collaborative group that includes a mix of big data, API, and full stack development teams. We are growing rapidly to help invent the future of Real Estate, with Machine Learning playing a critical role in that growth. 

 

This position is located in Washington, D.C. and offers a hybrid schedule of 3 days onsite, 2 days remote. 

 

RESPONSIBILITIES 

  • Collaborate on the continued improvement of CoStar’s cloud-based machine learning environment. 
  • Design, build, train, deploy and evaluate machine learning models that handle large amounts of data. 
  • Collaborate with other engineers, product owners, and leadership to create ML solutions that solve practical problems and improve our customer’s experience. 
  • Gain an understanding of the CoStar business and how ML can improve things. 

 

BASIC QUALIFICATIONS 

  • Bachelor’s Degree required from an accredited, not for profit university or college, preferably in Computer Science, Machine Learning, or a related field. A master’s or PhD is highly desirable. 
  • A track record of commitment to prior employers 
  • 5+ years of professional experience as a Machine Learning Engineer, Data Scientist or in a related role for candidates with a master’s or bachelor’s degree, or 3+ years of experience for candidates with a PhD. 
  • Extensive programming experience with Python and proficiency in ML libraries such as TensorFlow, PyTorch, and Scikit-learn. 
  • Experience of deploying end-to-end at-scale ML solutions using cloud-based architectures, including data ingestion, model training, model evaluation, and inference pipelines 
  • Strong understanding of fundamental machine learning concepts and ability to devise custom approaches to solve practical problems using machine learning 

 

PREFERRED SKILLS 

  • Strong domain expertise in natural language processing  
  • Experience with AI engineering using proprietary or open source LLMs, including the use of tools such as HuggingFace 
  • Experience with databases, such as DynamoDB, and cloud ML platforms, such as Databricks 

 

What’s in it for You 

When you join CoStar Group, you’ll experience a collaborative and innovative culture working alongside the best and brightest to empower our people and customers to succeed. 

We offer you generous compensation and performance-based incentives. CoStar Group also invests in your professional and academic growth with internal training, tuition reimbursement, and an inter-office exchange program. 

Our benefits package includes (but is not limited to): 

  • Comprehensive healthcare coverage: Medical / Vision / Dental / Prescription Drug 
  • Life, legal, and supplementary insurance 
  • Virtual and in person mental health counseling services for individuals and family 
  • Commuter and parking benefits 
  • 401(K) retirement plan with matching contributions 
  • Employee stock purchase plan 
  • Paid time off 
  • Tuition reimbursement 
  • On-site fitness center and/or reimbursed fitness center membership costs (location dependent), with yoga studio, Pelotons, personal training, group exercise classes 
  • Access to CoStar Group’s Diversity, Equity, & Inclusion Employee Resource Groups 
  • Complimentary gourmet coffee, tea, hot chocolate, fresh fruit, and other healthy snacks 

We welcome all qualified candidates who are currently eligible to work full-time in the United States to apply.  However, please note that CoStar Group is not able to provide visa sponsorship for this position. 

 

This position offers a base salary range of $142,000 - $204,000, based on relevant skills and experience and includes a generous benefits plan.

#LI-Hybrid

#LI-AR

CoStar Group is an Equal Employment Opportunity Employer; we maintain a drug-free workplace and perform pre-employment substance abuse testing

Salary

$142,000 - $204,000

Yearly based

Location

US-DC Washington DC

Job Overview
Job Posted:
3 months ago
Job Expires:
Job Type
Full Time

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