Machine Learning Engineer

Machine Learning Engineer,

This position is located in Arlington, VA and will have a 4-day onsite schedule (Monday-Thursday) with Fridays work from home.

• Collaborate on the continued improvement of CoStar’s cloud-based machine learning environment
• Design, build, test and deploy scalable, reusable and maintainable 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

• Bachelor’s degree required from an accredited, not-for-profit, in-person college/university
• A track record of commitment to prior employers
• 5+ years of professional development experience as Machine Learning Engineer, Data Scientist or related role
• 3+ years of programming experience with Python
• Experience with recommendation systems and (preferably) computer vision
• Strong foundations in ML concepts including supervised/unsupervised learning, model evaluation, feature engineering, and familiarity with deep learning frameworks (PyTorch or Tensor Flow)

• Experience with ML cloud tools such as Databricks, Amazon Personalize, Sage Maker
• Experience with SQL-based relational databases (e.g. AWS RDS) or document-based databases (e.g. Dynamo
  
  DB)
• Experience solving streaming and batch data processing problems at scale
• Experience building, deploying and optimizing ML models

• Comprehensive healthcare coverage:
  Medical / Vision / Dental / Prescription Drug
• Life, legal, and supplementary insurance
• Commuter and parking benefits
• 401(K) retirement plan with matching contributions
• Employee stock purchase plan
• Paid time off
• Tuition reimbursement
• Complimentary gourmet coffee, tea, hot chocolate, prepared foods, fresh fruit, and other healthy snacks

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