Machine Learning Engineer - Remote

About The Company

Lennar is one of the nation's leading homebuilders, dedicated to making a positive impact and creating an extraordinary experience for homeowners, communities, and associates. The company is committed to building quality homes, providing exceptional customer service, giving back to local communities, and fostering a culture of opportunity and growth for its employees. Recognized as a Fortune 500® company and consistently ranked among the top homebuilders in the United States, Lennar has established itself as a trusted name in the industry. The company's mission revolves around delivering innovative housing solutions while maintaining a focus on sustainability, affordability, and community development. With a strong reputation for integrity and excellence, Lennar continues to expand its footprint across the country, ensuring that every home built meets the highest standards of quality and craftsmanship.

About The Role

We are seeking a highly skilled Lead Machine Learning (ML) Engineer to join our Applied AI & Data Science team. This pivotal role involves owning and evolving the infrastructure that transforms data science and ML models from experimental notebooks into scalable, reliable production systems. The ideal candidate will possess deep expertise in MLOps, with a strong background in designing model serving architectures for both batch and real-time inference. You will be responsible for building durable model registries, versioning practices, and retraining pipelines that facilitate seamless model updates and monitoring. The role requires hands-on experience with AWS SageMaker, MLflow, Weights & Biases, and related tooling to ensure the deployment, operation, and maintenance of ML systems are robust and scalable. You will collaborate closely with data scientists, AI engineers, and platform teams to establish standards and best practices that accelerate model deployment cycles, improve operational reliability, and support the company's strategic AI initiatives. This role offers an exciting opportunity to influence how ML models are integrated into business processes across multiple divisions, ultimately contributing to Lennar’s mission of building zero-defect homes and exceptional customer experiences.

Qualifications

• Bachelor's degree or higher in Computer Science, Engineering, or a related technical field
• 7+ years of software engineering experience, including ownership of services or platforms in a cloud environment
• 5+ years of hands-on experience with MLOps or ML platform development, including deploying, monitoring, and retraining models at scale
• Deep expertise with AWS SageMaker, including SageMaker Unified Studio
• Proficiency with experiment tracking, model registries, and retraining workflows using MLflow, Weights & Biases, or similar tools
• Strong Python programming skills, with experience in writing modular, production-ready code
• Experience with infrastructure-as-code tools such as Terraform
• Solid understanding of batch and real-time inference patterns, including latency, throughput, and operational tradeoffs
• Ability to collaborate effectively with data scientists, understanding their workflows and translating needs into scalable platform solutions
• Proactive approach to work, capable of operating independently in ambiguous environments

Responsibilities

• Design, build, and maintain the ML platform surface used by data science teams, including model packaging, deployment, inference, and observability components
• Establish and promote standards, patterns, and reusable components for ML model deployment and operation across the organization
• Mentor data scientists and engineers on best practices in production ML, conducting code reviews and providing technical guidance
• Own and optimize model serving infrastructure on AWS SageMaker, including batch inference, real-time endpoints, and serverless options based on workload requirements
• Develop and manage model registries, version control, and workflows for model promotion from development to production with full lineage and auditability
• Implement and operate retraining pipelines utilizing MLflow, Weights & Biases, and orchestration tools, automating retraining triggers, experiment tracking, and model evaluation
• Build monitoring and alerting systems for production models, focusing on drift detection, performance degradation, data quality issues, and operational anomalies
• Write clean, modular code in Python and infrastructure-as-code scripts (Terraform), adhering to software engineering best practices including testing and version control
• Collaborate with data scientists to streamline workflows, reduce time-to-production, and enhance model reliability and confidence
• Partner with data/platform engineering teams to ensure seamless integration of feature pipelines, model artifacts, and inference services within the broader data ecosystem

Benefits

• Opportunity to make a meaningful impact within one of the largest homebuilders in the United States
• Access to a corporate culture focused on growth, development, and innovation
• Freedom to experiment with new ideas and technologies
• End-to-end ownership of projects with visibility across multiple divisions
• Remote work flexibility, with preferred locations including Miami, FL; Bentonville, AR; and Dallas, TX
• Comprehensive healthcare coverage including medical, dental, and vision plans
• 401(k) retirement plan with company matching up to 5%
• Paid parental leave and employee assistance programs
• Educational assistance programs and adoption support up to $30,000
• Generous paid time off including vacation, holidays, sick leave, and personal days
• Additional perks such as home purchase discounts and referral bonuses

Equal Opportunity

Lennar is an equal opportunity employer and is committed to creating a diverse and inclusive workplace. We comply with all applicable federal, state, and