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Lead Machine Learning Engineer I, Lifetime Value

Caret Holdings, Inc. · Remote (United States), United States · Remote · Active · $164,000–$205,000 / year · Rippling ATS

Job facts

FieldValue
CompanyCaret Holdings, Inc.
TitleLead Machine Learning Engineer I, Lifetime Value
Normalized title-
Department / teamDS Marketing
LocationUnited States
Work modelRemote / Remote
Employment typeFull Time
Salary$164,000–$205,000 / year
Statusactive
ATS providerRippling ATS
Posted / first seen2026-05-28 / 2026-05-29
Changed / last seen2026-06-06 / 2026-06-06

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Company jobsActive postings from Caret Holdings, Inc..Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Rippling ATS.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in DS Marketing.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyCaret Holdings, Inc.
Source71cf69f9-271e-48fd-bac9-97d57a11d075
ATS providerRippling ATS

Description

company At Root, we’re on a mission to improve the lives of our customers by offering better insurance solutions. We challenge ourselves to think differently in order to reimagine insurance to make it smarter, more equitable, and a better experience for all. We strive to “unbreak” the archaic insurance industry by using data and technology in innovative new ways. We believe we must be steadfast in our commitments to research, experimentation, and disciplined data-driven decision making in order to build products our customers love. role The Opportunity We believe that a disruptive insurance company must have a principled quantitative framework at its foundation. At Root, we are committed to the rigorous development and effective deployment of modern statistical machine learning methods to problems in the insurance industry. Root is seeking a Lead Machine Learning Engineer I to help build the systems and workflows that power our customer lifetime value modeling ecosystem. In this role, you will partner closely with data scientists, engineers, and business teams to build scalable machine learning systems that support high-impact decision-making across Marketing, Finance, Product, and Customer Experience. You will help accelerate the path from experimentation to production while improving the reliability and operational maturity of Root’s ML ecosystem. This role focuses on building the infrastructure, tooling, and operational patterns that allow machine learning systems to scale reliably in production. You will help shape the foundations that enable statistical models, simulations, and forecasts to drive measurable business impact across the organization. The ideal candidate is a machine learning engineer who enjoys building high-leverage systems, improving how technical teams work, and enabling machine learning to operate reliably at scale. Root is a “work where it works best” company, meaning we will support you working in whatever location works best for you across the U.S. Salary Range: $164,000 - $205,000 (Eligible for Competitive Bonus & Equity Offering) How You Will Make an Impact Build and improve the systems that power customer lifetime value modeling, from development and deployment through monitoring and production support. Partner with data scientists to productionize statistical models, simulations, and forecasting workflows that support decision-making across the business. Accelerate the path from research to production through scalable infrastructure, reliable workflows, and reusable tooling. Improve the ML development experience by building better operational patterns and advancing production-ready ML practices. Develop tools and services that help stakeholders evaluate model performance, understand business impact, and trust model outputs in production. Collaborate with technical and business partners to solve high-value problems and improve the reliability and scalability of ML systems. Share best practices through mentorship, documentation, and clear communication around technical decisions, tradeoffs, and operational considerations. What You Will Need to Succeed BS in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. 5+ years of experience designing, building, deploying, and maintaining machine learning systems and ML model pipelines in partnership with data scientists. Strong Python and software engineering fundamentals, with the ability to build maintainable ML systems and production-quality code. Experience building and operating production ML systems, including deployment, monitoring, debugging, and workflow orchestration. Ability to design reproducible systems with clear lineage, versioning, and operational visibility across complex ML workflows. Comfort working in ML systems with interconnected components, simulation-driven logic, and embedded business rules. Strong judgment around model evaluation, code quality, system reliability, and maintainable engineering tradeoffs. Experience with cloud-based ML infrastructure and data platforms such as AWS, GCP, or Azure. Experience with infrastructure as code, such as Terraform. Clear communication skills and the ability to explain technical tradeoffs to both technical and non-technical audiences. Nice to Have MS or PhD in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. Familiarity with customer lifetime value forecasting, simulation workflows, or Forecast vs. Actual analysis. Experience with insurance or regulated financial products. Exposure to ML and data tooling, orchestrators, and platforms such as MLflow, Airflow, Dagster, Snowflake, Databricks, dbt, and Spark Experience building shared ML infrastructure, developer tooling, or reusable systems that improve data science productivity. As part of Root's interview process, we kindly ask that all candidates be on camera for virtual interviews. This helps us create a more personal and engaging experience for both you and our interviewers. Being on camera is a standard requirement for our process and part of how we assess fit and communication style, so we do require it to move forward with any applicant's candidacy. If you have any concerns, feel free to let us know once you are contacted. We’re happy to talk it through. Please see our Privacy Notice available HERE for more information on how we process your personal data. Consistent with the Americans with Disabilities Act (ADA) and the Civil Rights Act of 1964, it is the policy of Root to provide reasonable accommodation when requested by a qualified applicant or candidate with a disability, unless such accommodation would cause an undue hardship for Root. The policy regarding requests for reasonable accommodation applies to all aspects of the hiring process. If reasonable accommodation is needed, please contact [email protected].

Full job record

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Source ID71cf69f9-271e-48fd-bac9-97d57a11d075
Board ID71cf69f9-271e-48fd-bac9-97d57a11d075
Providerrippling
Provider Job Keydffb8ae0-e17c-49a1-8303-4ecc2a66e537
TitleLead Machine Learning Engineer I, Lifetime Value
Normalized Title—
Statusactive
Activeyes
Location TextRemote (United States), United States
DepartmentDS Marketing
Team—
Employment Typefull_time
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region—
City—
Salary RawSalary Range: $164,000 - $205,000 (Eligible for Competitive Bonus & Equity Offering) How You Will Make an Impact
Salary Min164,000
Salary Max205,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://ats.rippling.com/joinroot/jobs/dffb8ae0-e17c-49a1-8303-4ecc2a66e537
Apply URLhttps://ats.rippling.com/joinroot/jobs/dffb8ae0-e17c-49a1-8303-4ecc2a66e537
First Seen At2026-05-29 07:16:19Z
Last Seen At2026-06-06 08:44:19Z
Last Checked At2026-06-06 08:44:19Z
Last Changed At2026-06-06 08:44:19Z
Inactive At—
Source Posted At2026-05-28 20:24:29Z
Source Updated At—
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Event Fields
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      "role": "<meta><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">The Opportunity</strong></b></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">We believe that a disruptive insurance company must have a principled quantitative framework at its foundation. At Root, we are committed to the rigorous development and effective deployment of modern statistical machine learning methods to problems in the insurance industry.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Root is seeking a </span><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Lead Machine Learning Engineer I</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> to help build the systems and workflows that power our customer lifetime value modeling ecosystem.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">In this role, you will partner closely with data scientists, engineers, and business teams to build scalable machine learning systems that support high-impact decision-making across Marketing, Finance, Product, and Customer Experience. You will help accelerate the path from experimentation to production while improving the reliability and operational maturity of Root’s ML ecosystem.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">This role focuses on building the infrastructure, tooling, and operational patterns that allow machine learning systems to scale reliably in production. You will help shape the foundations that enable statistical models, simulations, and forecasts to drive measurable business impact across the organization.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">The ideal candidate is a machine learning engineer who enjoys building high-leverage systems, improving how technical teams work, and enabling machine learning to operate reliably at scale.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Root is a “work where it works best” company, meaning we will support you working in whatever location works best for you across the U.S.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Salary Range:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> $164,000 - $205,000 </span><span style=\"color:rgb(32,32,34);font-size:11pt;white-space:pre-wrap;\">(Eligible for Competitive Bonus &amp; Equity Offering)</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">How You Will Make an Impact</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Build and improve the systems that power customer lifetime value modeling, from development and deployment through monitoring and production support.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Partner with data scientists to productionize statistical models, simulations, and forecasting workflows that support decision-making across the business.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Accelerate the path from research to production through scalable infrastructure, reliable workflows, and reusable tooling.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Improve the ML development experience by building better operational patterns and advancing production-ready ML practices.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Develop tools and services that help stakeholders evaluate model performance, understand business impact, and trust model outputs in production.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Collaborate with technical and business partners to solve high-value problems and improve the reliability and scalability of ML systems.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Share best practices through mentorship, documentation, and clear communication around technical decisions, tradeoffs, and operational considerations.&nbsp;</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">What You Will Need to Succeed</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">BS in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">5+ years of experience designing, building, deploying, and maintaining machine learning systems and ML model pipelines in partnership with data scientists.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Strong Python and software engineering fundamentals, with the ability to build maintainable ML systems and production-quality code.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience building and operating production ML systems, including deployment, monitoring, debugging, and workflow orchestration.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Ability to design reproducible systems with clear lineage, versioning, and operational visibility across complex ML workflows.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Comfort working in ML systems with interconnected components, simulation-driven logic, and embedded business rules.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Strong judgment around model evaluation, code quality, system reliability, and maintainable engineering tradeoffs.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience with cloud-based ML infrastructure and data platforms such as AWS, GCP, or Azure.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience with infrastructure as code, such as Terraform.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Clear communication skills and the ability to explain technical tradeoffs to both technical and non-technical audiences.</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Nice to Have</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">MS or PhD in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Familiarity with customer lifetime value forecasting, simulation workflows, or Forecast vs. Actual analysis.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience with insurance or regulated financial products.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Exposure to ML and data tooling, orchestrators, and platforms such as MLflow, Airflow, Dagster, Snowflake, Databricks, dbt, and Spark</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience building shared ML infrastructure, developer tooling, or reusable systems that improve data science productivity.&nbsp;</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">As part of Root's interview process, we kindly ask that all candidates be on camera for virtual interviews. This helps us create a more personal and engaging experience for both you and our interviewers. Being on camera is a standard requirement for our process and part of how we assess fit and communication style, so we do require it to move forward with any applicant's candidacy. If you have any concerns, feel free to let us know once you are contacted. We’re happy to talk it through.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(29,28,29);white-space:pre-wrap;\">Please see our Privacy Notice available&nbsp;</span><a href=\"http://inc.joinroot.com/california-job-applicant-privacy-notice/\" target=\"_blank\" class=\"css-173makr-linkStyle\" style=\"color:rgb(30,74,169);cursor:pointer;\"><span style=\"color:rgb(29,28,29);white-space:pre-wrap;\">HERE</span></a><span style=\"color:rgb(29,28,29);white-space:pre-wrap;\">&nbsp;for more information on how we process your personal data.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(29,28,29);white-space:pre-wrap;\">Consistent with the Americans with Disabilities Act (ADA) and the Civil Rights Act of 1964, it is the policy of Root to provide reasonable accommodation when requested by a qualified applicant or candidate with a disability, unless such accommodation would cause an undue hardship for Root. The policy regarding requests for reasonable accommodation applies to all aspects of the hiring process. If reasonable accommodation is needed, please contact [email protected].</span></p>",
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GET https://api.bluedoor.sh/job-postings/v1/jobs/dcd4d1bdd8b1e2e951f917b98fe2095395d9d8fa?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/1ffc0c5b-007d-44a0-9ead-68fdbfa31142JSON
GET https://api.bluedoor.sh/job-postings/v1/sources/71cf69f9-271e-48fd-bac9-97d57a11d075JSON
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