1 месяц назад
MLOps Engineer (Azure)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
MLOps Engineer (Azure): Building and operating end-to-end machine learning pipelines and production infrastructure for proprietary ML models and LLM integrations with an accent on deployment, observability, and governance. Focus on model serving, data drift detection, LLM provider and cost management, prompt versioning, and reliable CI/CD-driven workflows.
Location: Bangalore, India
Company
is a global RegTech company providing AI-powered SaaS solutions for regulatory intelligence in the financial services industry.
What you will do
- Design, automate, and operate end-to-end ML training, evaluation, and deployment pipelines with Azure AI Foundry and Azure Machine Learning.
- Manage containerized model endpoints, versioning, traffic management, and rollback mechanisms across environments.
- Implement model performance monitoring, data drift detection, alerting, and production observability.
- Govern LLM providers including OpenAI, Azure OpenAI, and Anthropic; manage API access, versioning, token consumption, and cost optimization.
- Maintain LLM gateway and prompt-versioning tools such as LangSmith or Helicone, and support experiment tracking and model registry practices.
- Collaborate with data scientists and engineers to build reliable production systems and improve platform reliability and cost efficiency.
Requirements
- 3–4 years of experience with machine learning, Azure, deployment, and pipelines.
- Experience building and operating production ML pipelines and model-serving infrastructure.
- Understanding of model monitoring, data drift detection, alerting, and LLM observability.
- Ability to apply CI/CD, infrastructure as code, automated testing, and reproducible experiment practices to ML workflows.
- Strong collaboration skills for working with data scientists, AI architects, and data engineers.
Culture & Benefits
- Work in a global team of more than 700 employees across 19 countries.
- Contribute to an AI-focused SaaS platform transforming regulatory compliance.
- Take ownership of establishing the MLOps discipline during platform consolidation following acquisitions.
- Join an inclusive, collaborative, and high-performing engineering environment.
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