Staff Machine Learning Engineer

About the Role

Key Responsibilities

• Take a leadership role in developing and deploying state-of-the-art machine learning solutions that power Realtor.com's products and business strategy.
• Build intelligent systems that optimize pricing, forecasting, and recommendation engines to improve understanding of the customer portfolio and drive revenue growth.
• Own the full ML lifecycle: from data exploration to model development, deployment, and continuous optimization.
• Develop scalable, production-ready ML models that support monetization, pricing optimization, and intelligent recommendations.
• Experiment and innovate by leveraging AI to enhance customer insights and improve home search and listing experiences.
• Mentor a team of talented machine learning engineers, guiding them in best practices for model development, deployment, and optimization.
• Collaborate with cross-functional teams, including product managers, analysts, data engineers, and leadership, to identify high-impact opportunities and translate them into AI-driven solutions.
• Deploy models at scale using modern cloud platforms (AWS/GCP), containerization (Docker), and ML frameworks like TensorFlow, PyTorch, or JAX.

Requirements

• Expertise in Applied ML with a PhD/MS in computer science, statistics, mathematics, operations research, or related fields.
• At least 2 years of relevant experience in data science, machine learning, or applied statistics, with a strong background in information retrieval, forecasting, recommendation systems, or related ML applications.
• Hands-on experience deploying ML models at scale using cloud platforms like AWS, Kubernetes, or similar.
• Proficiency in Python, Spark, TensorFlow/PyTorch, and SQL.
• Experience with large-scale distributed systems is a plus.
• Strong creative thinking and problem-solving skills to tackle complex business challenges.
• Excellent communication skills to articulate ML concepts to both technical and non-technical stakeholders.

Nice to Have

• Experience with causal ML is a plus.

Qualifications

• PhD or MS in computer science, statistics, mathematics, operations research, or related fields.
• 2+ years of relevant experience in data science, machine learning, or applied statistics.

Benefits & Perks

• Medical, dental, vision, and Rx coverage.
• Family forming benefits.
• 13 Paid Holidays and Flexible Time Off.
• 8 hours of paid Volunteer Time off.
• Immediate eligibility into Company 401(k) plan with 3.5% company match.
• Tuition Reimbursement program for degreed and non-degreed programs.
• Financial Planning Sessions.
• Student Debt Retirement Savings Match program.
• Free snacks and refreshments in each office location.