Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Чётко очерченная роль в MLOps у крупной компании связана с современными AI-задачами и хорошим пакетом льгот, но зарплата не указана, а спонсорства визы нет.
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Без спонсорства визыЗарплата не указанаСовременный стекПонятные задачиХорошие льготы
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Machine Learning Operations-Engineer II (MLOps): Building and operating cloud-based MLOps capabilities and production ML pipelines for analytical and generative AI models with an accent on automation, scalability, governance, and production readiness. Focus on operationalizing LLM and RAG solutions, designing cloud-native event-driven architectures, and ensuring secure, compliant model lifecycle management.
Location: Irving, Texas, United States; hybrid work with two days per week in the office
Company
hirify.global is General Motors’ captive finance subsidiary, providing retail, lease, and commercial auto financing solutions across North America, South America, and the Asia Pacific region.
What you will do
Build and maintain scalable cloud-based MLOps platforms for analytical and generative AI models.
Develop production ML pipelines covering training, deployment, monitoring, governance, and lifecycle automation.
Improve the speed, quality, and reliability of model development, experimentation, and operations.
Define and enforce MLOps standards in partnership with model governance, security, and compliance teams.
Collaborate with data science, engineering, IT, and business stakeholders to deliver secure and high-impact AI solutions.
Research and prototype new MLOps capabilities that create measurable business value.
Requirements
2–4 years of experience as a data scientist, machine learning engineer, or in a similar quantitative field.
Hands-on experience across the full ML/MLOps lifecycle, including MLflow and platforms such as Databricks, Azure Machine Learning, or SageMaker.
Experience operationalizing generative AI solutions, including LLM patterns such as RAG, prompt and version management, evaluation, safety, and monitoring.
Strong software and cloud engineering fundamentals, including CI/CD, Docker, Kubernetes, and AKS.
Experience with event-driven and streaming architectures, cloud-native design patterns, Python, SQL, Spark, Delta, and lakehouse platforms.
High school diploma or equivalent required; a master’s degree or PhD in computer science, engineering, analytics, mathematics, or a related discipline is preferred. Visa sponsorship is not available.
Culture & Benefits
Flexible hybrid work environment with two days per week in the office.
401(k) matching and a benefits package available from day one.
Fully paid 12-week bonding leave for new parents.
Tuition assistance, training, community service pay, and nine company holidays.
GM employee auto discount and bonus eligibility.
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