Senior MLOps Engineer, TheGuarantors
$200-220k
1-5 days a week in office
Financial & insurance solutions for renters and landlords
Be an early applicant
Financial & insurance solutions for renters and landlords
201-500 employees
Be an early applicant
$200-220k
1-5 days a week in office
201-500 employees
Company mission
TheGuarantors' mission is to unlock opportunity and financial advantage for everyone involved in residential and commercial leasing.
Role
Who you are
- 5+ years of experience in MLOps, ML Engineering, or DevOps, with a strong record of deploying machine learning models at scale
- Ph.D. in Math, Engineering, Statistics, Economics preferred
- Proficiency 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 strategies
- Familiarity 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 research
- Knowledge of data privacy and compliance requirements for deploying models in regulated industries
- Excellent communication skills and a collaborative mindset for working cross-functionally across technical and business teams
- Bonus: Background in fintech, insurance, pricing analytics, or risk modeling
What the job involves
- 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
- Design and manage robust ML/AI pipelines to support scalable deployments across Pricing, Risk, Claims, GTM, and Sales
- Collaborate with data scientists to operationalize supervised, unsupervised, and optimization models in real-world production systems
- Implement reusable infrastructure such as centralized feature stores, model registries, and experiment tracking tools
- Build intelligent exception handling frameworks for automated model recovery, schema drift detection, and fallbacks
- Architect infrastructure that supports dynamic pricing engines, loss prediction models, claims triage algorithms, and real-time lead scoring
- Support operations research use cases by integrating solvers and simulation frameworks into model pipelines
- Monitor model health using live dashboards and alerts for data drift, bias, and latency across both batch and real-time scoring
- Enable rapid experimentation through reproducible workflows and automated CI/CD tailored for ML
- Embed governance practices such as audit logging, explainability tooling, and PII protection into the MLOps layer
- Future-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 turnaround
- Contribute to the evolution of our AI Platform strategy and evaluate next-gen MLOps tools to improve developer velocity and system resilience
- Act as a mentor and thought partner across engineering and data teams to uplift the organization's model delivery capabilities
Our take
Home rental rates across the US are soaring. On average, rent went up by over 10% in a single year between 2021 and 2022, while in some cities that increase is as much as 40%. Renters are now struggling more than ever to qualify for homes and afford security deposits, which also impacts landlords who lack security.
TheGuarantors, which is a licensed insurance agent and broker bridges this gap by acting as a co-signer, then offering to cover and underwrite security deposits if necessary in exchange for a percentage fee of the monthly rent.
There’s been a lot of movement in the rental startups space of late, with venture capital being poured into companies like rent-to-own Divvy and rent now, pay later startup Jetty.
TheGuarantors, however, has seen immense user uptake on its platform and has won the capital backing of Portage Venture, which it intends to use to scale both its product offering and staff headcount. This, plus B Corp certification awarded in 2024, will help TheGuarantors expand its market visibility.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Apr 2022
$50m
SERIES C
Dec 2021
$50m
SERIES C
Total funding: $138.3m
Company benefits
- Remote work: All our roles are 100% remote which allows the flexibility for our employees as we navigate the recent changes to our work environments.
- Opportunities to make an impact within a fast growing company
- Medical, Dental, & Vision insurance (beginning day one)
- 401(k)
- Competitive salary
- Generous PTO and paid holidays
Company HQ
World Trade Center, New York, NY
Leadership
Julien Bonneville
(Co-Founder & CEO)Was a Founding Partner of consulting and market data firm Sanisphere, which provided health and pharmaceutical intelligence in developing countries, then an Associate at McKinsey & Company before joining IMS Health as a Consultant.
Bob Schmidt
(Co-Founder & CRO)Founded and led Donnin Publishing from 1990-2013, before founding Rentassure Agency where they served as CMO, CEO, and Chairman. Before TheGuarantors they were a Leasing Manager in the Long Island City Project for TF Cornerstone.
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