Company Name: TheGuarantors

Job Details: Hiring,Remotely,in,United,States,Remote,or,Hybrid,200K-220K,Annually,Senior,level

Job Url: https://builtin.com/job/senior-mlops-engineer/7590985

Job Description: TheGuarantors is a cutting edge fintech company setting the standard in rent coverage with unrivaled insurance products. With a deep understanding of owner, operator, and renter needs, we believe renters deserve better access to the home of their dreams and operators deserve greater protection and growth opportunities. That’s why we’re leveraging our expertise in real estate and using AI-based technology to help operators qualify renters faster while mitigating the risk of rental income loss. With $5B+ in rent and deposits guaranteed, we work with 9 of the country’s top 10 operators and have been named one of Inc. 5000’s fastest-growing companies, one of Forbes’ Best Startup Employers, and one of Deloitte’s Technology Fast 500.The OpportunityWe are building a next-generation AI/ML operating model at TheGuarantors—anchored by a centralized AI Platform & MLOps team and empowered domain-focused squads across Pricing, Risk, Claims, GTM, and Sales.As a Senior MLOps Engineer, you will be a foundational member of the platform team, building scalable, governed infrastructure that accelerates the development and deployment of machine learning and operations research models. You’ll work closely with data scientists and engineers to ensure fast, safe, and reliable delivery of high-impact models—from pricing elasticity and dynamic underwriting to claims automation and lead scoring.LocationRemote What You’ll DoDesign and manage robust ML/AI pipelines to support scalable deployments across Pricing, Risk, Claims, GTM, and SalesCollaborate with data scientists to operationalize supervised, unsupervised, and optimization models in real-world production systemsImplement reusable infrastructure such as centralized feature stores, model registries, and experiment tracking toolsBuild intelligent exception handling frameworks for automated model recovery, schema drift detection, and fallbacksArchitect infrastructure that supports dynamic pricing engines, loss prediction models, claims triage algorithms, and real-time lead scoringSupport operations research use cases by integrating solvers and simulation frameworks into model pipelinesMonitor model health using live dashboards and alerts for data drift, bias, and latency across both batch and real-time scoringEnable rapid experimentation through reproducible workflows and automated CI/CD tailored for MLEmbed governance practices such as audit logging, explainability tooling, and PII protection into the MLOps layerFuture-proof our AI/ML stack with modular, scalable, cloud-native components (e.g., Terraform, Kubernetes, SageMaker, MLflow)Partner with domain squads to align AI deployments with KPIs such as conversion uplift, pricing precision, loss ratio, and claims turnaroundContribute to the evolution of our AI Platform strategy and evaluate next-gen MLOps tools to improve developer velocity and system resilienceAct as a mentor and thought partner across engineering and data teams to uplift the organization's model delivery capabilities What You Bring5+ years of experience in MLOps, ML Engineering, or DevOps, with a strong record of deploying machine learning models at scalePh.D. in Math, Engineering, Statistics, Economics preferredProficiency in Python and orchestration tools (Airflow, Prefect, Dagster), plus experience with model lifecycle tooling (MLflow, SageMaker, Vertex AI)Hands-on experience with containerization (Docker), orchestration (Kubernetes/EKS), and infrastructure-as-code (Terraform, CloudFormation)Deep understanding of the machine learning lifecycle, including feature engineering, testing, observability, and rollback strategiesFamiliarity with exception handling patterns in production ML (e.g., fail-soft design, data quality validation, anomaly flagging)Experience supporting or integrating optimization libraries, solvers, and simulation workflows for operations researchKnowledge of data privacy and compliance requirements for deploying models in regulated industriesExcellent communication skills and a collaborative mindset for working cross-functionally across technical and business teamsBonus: Background in fintech, insurance, pricing analytics, or risk modelingBenefitsOpportunities to make an impact within a fast growing companyMedical, dental, & vision insurance, beginning day oneHealth savings account with employer contributionFlexible spending accounts (healthcare, dependent care, commuter)401(k)Generous PTO and paid holidaysFlexible working hoursPaid parental leaveCompany sponsored short and long term disabilityBase SalaryThe base salary range is between $200,000 - $220,000 annually.Base salary does not include other forms of compensation or benefits. Final offer amounts are determined by multiple factors, including prior experience, expertise, location and current market data and may vary from the range above.Stay in TouchDoes this role not quite match your skills, but you’re still interested in what we're doing? Stay In Touch to be one of the first to hear about future opportunities!TheGuarantors is an Equal Opportunity Employer. We celebrate diversity and are committed to an inclusive environment for all.