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Senior Engineer, Machine Learning/AI Ops

National Debt Relief, LLC.

Trabajo remoto

Ubicación
Remote (United States)
Retribución
USD 150500-173000 per annual
Jornada
Full Time
Publicado
13 oct 2026

Confirma que la oferta sigue abierta y revisa sus condiciones en el sitio web de la empresa antes de solicitar el puesto.

Descripción del puesto

La interfaz está en español. Los títulos y las descripciones de las empresas se mantienen en el idioma original de publicación, que puede ser inglés.

Overview National Debt Relief (NDR) is seeking a Senior Engineer, ML & AI Ops to build and operate the AWS platform supporting our machine learning models, internal AI tools, and event-driven integrations. This role partners closely with Data Science, Data Engineering, Analytics, Product, and other engineering teams. NDR’s ML platform is being built out on AWS now, and this role extends it. The role spans model training and inference, real-time APIs, change data capture, and secure integrations between internal and third-party systems. The ideal candidate combines deep AWS and infrastructure-as-code experience with strong software engineering fundamentals. They have built reliable production services, integrations, and ML systems where security, observability, and auditability are essential Responsibilities Design, build, and operate the AWS infrastructure and services behind NDR’s ML models, internal AI tools, and event-driven integrations. Build and operate event-driven integrations and CDC pipelines between internal and third-party systems, including Salesforce and platforms such as Braze. Design integrations for reliability and recoverability, including idempotency, replay, schema evolution, and out-of-order events. Build and maintain containerized inference APIs and backend services with secure, versioned interfaces and production-grade performance. Manage infrastructure in Terraform across multiple AWS accounts and environments using reusable modules and CI-gated workflows. Build ML workflows for training, retraining, scoring, and inference, and partner with Data Science to create repeatable paths from experiment to production. Implement observability across ML systems, AI tools, and integration services, including logging, metrics, alerting, and model monitoring. Support secure operation of internal LLM and agentic systems, including Amazon Bedrock, with appropriate access controls, auditing, and data protections. Partner with Data Engineering on Snowflake datasets, data access, and governance supporting ML and operational workflows. Lead incident response, participate in on-call, and contribute runbooks, reusable patterns, and platform engineering standards. Qualifications Education/Experience: 6+ years in MLOps, platform engineering, DevOps/SRE, or backend engineering, with significant experience supporting ML, data, or event-driven production workloads. Bachelor’s degree in a relevant technical field, required. Deep, hands-on AWS experience designing and operating production workloads across compute, messaging, and security. Strong experience building event-driven integrations with third-party APIs, including change data capture. Experience with Terraform and infrastructure-as-code across multi-environment production systems. Hands-on experience deploying and operating ML models, including batch and real-time serving, versioning, and monitoring. Experience with containers, CI/CD, and safe production deployment practices. Experience operating PostgreSQL for production services, including schema migrations, indexing, and correctness under concurrent writes. Required Skills/Abilities: Required Skills: Strong professional Python experience building and operating production APIs, services, and integrations. High autonomy and strong communication skills, with the ability to operate from desired outcomes rather than prescribed approaches and influence platform engineering standards. Preferred Skills: Experience operating or securing internal LLM-based or agentic systems. Experience with ML observability, experiment tracking, or drift detection tooling. Hands-on Snowflake experience supporting ML or production data workloads. Experience in financial services, fintech, or another regulated industry. National Debt Relief Role Qualifications: Computer competency and ability to work with a computer. Prioritize multiple tasks and projects simultaneously. Exceptional written and verbal communication skills. Punctuality expected, ready to report to work on a consistent basis. Attain and maintain high performance expectations on a monthly basis. Work in a fast-paced, high-volume setting. Use and navigate multiple computer systems with exceptional multi-tasking skills. Remain calm and professional during difficult discussions. Take constructive feedback. Available for full-time position. Compensation Information Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for each position across the US. Within the range, individual pay is determined by work location, job-related skills, experience, and relevant education or training. This good faith pay range is provided in compliance with NYC law and the laws of other jurisdictions that may require a salary range in job postings. The salary for this position is $150,500.00 to $173,000.00.About National Debt Relief National Debt Relief was founded in 2009 with the goal of helping an expanding number of consumers deal with overwhelming debt. We are one of the most-trusted and best-rated consumer debt relief providers in the United States. As a leading debt settlement organization, we have helped over 450,000 people settle over $10 billion of debt, while empowering them to lead a healthier financial lifestyle and feel free to live their best life. At National Debt Relief, we treat our clients like real people. Our purpose is to elevate, empower, and transform their lives. Rated A+ by the Better Business Bureau, our goal is to help individuals and families get out of debt with the least possible cost through conducting financial consultations, educating the consumer and recommending the appropriate solution. We become our clients' number one advocate to help them reestablish financial stability as quickly as possible. Want to learn more about who we are? Connect with us on social! Benefits National Debt Relief is a team-oriented environment full of rewards and growth opportunities for our employees. We are dedicated to our employee's success and growth within the company, through our employee mentorship and leadership programs. Our extensive benefits package includes: Generous Medical, Dental, and Vision Benefits 401(k) with Company Match Paid Holidays, Volunteer Time Off, Sick Days, and Vacation 12 weeks Paid Parental Leave Pre-tax Transit Benefits No-Cost Life Insurance Benefits Voluntary Benefits Options ASPCA Pet Health Insurance Discount Wellness Incentive Program National Debt Relief is a certified Great Place to Work®! National Debt Relief is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other status protected by law. For information about our Employee Privacy Policy, please see hereFor information about our Applicant Terms, please see here Originally posted on Himalayas

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Preguntas sobre la búsqueda de empleo

¿Por qué algunas ofertas están en inglés?

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Prueba un título más general o una sola competencia y elimina los filtros de uno en uno. Los nombres de los puestos varían entre empresas. Si una oferta concreta ha desaparecido, busca su referencia en la página de empleo de la empresa; ampliar los filtros no recupera una vacante cerrada.

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¿Cómo adapto el currículum y la carta de presentación?

Relaciona los requisitos con proyectos, tareas y resultados que puedas explicar. Destaca lo relevante sin inventar experiencia ni copiar competencias que no tienes. En la carta, explica tu interés y aporta un ejemplo concreto. Respeta el idioma y el formato pedidos y revisa ambos documentos antes de enviarlos.