Lennar
Lead Machine Learning Engineer- REMOTE
Rol remoto de Lead Machine Learning Engineer con fit claro de ubicación del candidato.
Publicado13 jun 2026
Países elegibles1 país aceptado
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Estados Unidos
Resumen del rol
Lead Machine Learning Engineer- REMOTE
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
We are Lennar
- A career with purpose.
- A career built on making dreams come true.
- A career built on building zero defect homes, cost management, and adherence to schedules.
Your Responsibilities on the Team
- Design, build, and set the ML platform surface used by our data science team—covering model packaging, deployment, batch and real-time inference, and observability.
- Establish and evangelize ML platform standards, patterns, and reusable components—raising the engineering bar for how ML models are built, deployed, and operated across the organization.
- Mentor data scientists and engineers on production ML practices, code review their platform-adjacent work, and serve as the technical authority on MLOps decisions.
- Own model serving infrastructure on AWS SageMaker (including SageMaker Unified Studio)—building patterns for batch inference jobs, real-time endpoints, and serverless inference depending on workload requirements.
- Build and maintain the model registry, version control, and promotion workflows that move models cleanly from development to staging to production with full lineage and auditability.
- Stand up and operate retraining pipelines using MLflow, Weights & Biases, and orchestration tools—automating retraining triggers, experiment tracking, model evaluation, and approval gates.
- Build monitoring and alerting for production models including drift detection, performance degradation, data quality issues, and latency or cost anomalies.
- Write clean, modular Python and infrastructure-as-code (Terraform) for ML platform components, applying software engineering best practices including testing, versioning, and code review.
- Partner closely with data scientists to make their workflow faster and more reliable—reducing time-to-production for new models and increasing confidence in models already in production.
- Collaborate with Data / Platform Engineering and AI Engineering counterparts to ensure feature pipelines, model artifacts, and inference services are integrated cleanly with the broader data and AI platform.
Requirements
- Bachelor’s degree or higher in Computer Science, Engineering, or a related technical field.
- 7+ years of software engineering experience, including meaningful production ownership of services or platforms in a cloud environment.
- 5+ years of hands-on MLOps or ML platform experience—deploying, monitoring, and retraining production models at scale.
- Strong hands-on experience with AWS SageMaker (Unified Studio strongly preferred), including model training jobs, endpoints, batch transform, and pipelines.
- Deep experience with experiment tracking, model registries, and retraining workflows using MLflow, Weights & Biases, or comparable tooling.
- Strong Python skills with a track record of writing modular, well-tested, production-ready code; experience with infrastructure-as-code (Terraform preferred).
- Solid understanding of both batch and real-time inference patterns, including the tradeoffs between latency, throughput, cost, and operational complexity.
- Proven ability to partner with data scientists—understanding their workflow, lowering friction, and translating modeling needs into reliable platform capabilities.
- Comfortable operating with autonomy in ambiguous environments—scoping work, setting realistic timelines, and raising blockers proactively without waiting to be asked.
- Bonus: Experience with feature stores, model gateways, GPU workloads, distributed training, model drift monitoring tools, or supporting both classical ML and LLM-based models on the same platform.
What we offer:
- The opportunity to deliver impact across one of the largest homebuilders in the United States.
- A corporate culture focused on growth and development.
- Freedom to try new impactful ideas.
- Ability to deploy your work to teams across 40+ divisions and interact directly with those teams.
- End-to-end project ownership.
- Occasional travel for team activities and meetings.
- Remote work schedule, with a preference for candidates based in Miami, FL; Bentonville, AR; or Dallas, TX.
- Healthcare (medical, dental, vision) and 401k matching
What we offer:
- This information is intended to be a general overview and may be modified by the company due to factors affecting the business.
What we offer:
- This position may be eligible for bonuses.
- This position may be eligible for commissions.
- This position will be eligible for the described benefits listed in the above section in accordance with Company Policy.
- This information is intended to be a general overview and may be modified by the Company due to factors affecting the business.
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