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Senior ML Infrastructure Engineer (DevOps)

Role overview

Qualifications

  • 24x7 on-call experience with high-load online services in production
  • Strong Linux systems skills with experience in Kubernetes, Docker, and infrastructure as code
  • Solid experience in Python, Git, and CI/CD
  • Familiarity with workflow orchestration tools such as Airflow or Databricks Workflows

Responsibilities

  • Keep real-time inference services healthy through alerting, live debugging, and fixing production incidents
  • Build and improve AWS infrastructure, including infrastructure as code, CI/CD pipelines, Kubernetes, Docker, and monitoring
  • Care for the GPU fleet including NVIDIA driver and CUDA upgrades and capacity management
  • Run real-time production data pipelines and orchestrate batch jobs

Key facts

Hard skills

About the company

EPAM Systems logo

EPAM Systems

IT Services & IT Consulting

Since 1993, EPAM Systems, Inc. (NYSE: EPAM) has used its software engineering expertise to become a leading global provider of digital engineering, cloud and AI-enabled transformation services, and a leading business and experience consulting partner for global enterprises and ambitious startups. We address our clients’ transformation challenges by fusing EPAM Continuum’s integrated strategy, experience and technology consulting with our 30+ years of engineering execution to speed our clients’ time to market and drive greater value from their innovations and digital investments. We make GenAI real with our AI LLM orchestration, testing and engineering solutions, EPAM DIAL, EPAM EliteA™ and EPAM AI/RUN™, respectively. We deliver globally, but engage locally with our expert teams of consultants, architects, designers and engineers, making the future real for our clients, our partners and our people around the world. We believe the right solutions are the ones that improve people’s lives and fuel competitive advantage for our clients across diverse industries. Our thinking comes to life in the experiences, products and platforms we design and bring to market. Added to the S&P 500 and the Forbes Global 2000 in 2021 and recognized by Glassdoor and Newsweek as a Top 100 Best Workplace, our multidisciplinary teams serve customers across six continents. We are proud to be among the top 15 companies in Information Technology Services in the Fortune 1000 and to be recognized as a leader in the IDC MarketScapes for Worldwide Experience Build Services, Worldwide Experience Design Services and Worldwide Software Engineering Services. Learn more at www.epam.com.

Company details

Company typeXLarge
IndustryIT Services & IT Consulting
Company size10001

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Job description

We are looking for a Senior ML Infrastructure Engineer who enjoys running systems in production. You will work side by side with our applied scientists: they build the models, and you own everything needed to run them reliably for millions of customers. Our team owns its infrastructure end to end, deployment and operations included, so your work is visible, and the ownership is real. Experience with 24x7 on-call rotations for high-load online services in production is required for this role. You will thrive here if you have been the person who gets paged and fixes things, rather than handing deployment and operations to a separate team. Responsibilities Keep real-time inference services healthy through alerting, live debugging and fixing of production incidents, rollbacks and postmortems, as part of a shared 24x7 on-call rotation Build and improve AWS infrastructure, including infrastructure as code, CI/CD pipelines, Kubernetes, Docker, autoscaling, monitoring, load testing and cost control Care for the GPU fleet through NVIDIA driver and CUDA upgrades, node provisioning and debugging, and capacity management Automate user access, including SSH credentials, service accounts and developer environments for the science team Run real-time production data pipelines, including streaming ingestion into an online feature store and serving features to low-latency endpoints Orchestrate batch jobs with Airflow or Databricks Workflows Partner with applied scientists to productionize their prototypes and keep them healthy Write and review production Python, including validating AI-generated code Requirements 24x7 on-call experience with high-load online services in production, including real incidents personally debugged and fixed live Strong Linux systems skills, with hands-on experience in Kubernetes, Docker and infrastructure as code Solid experience in Python, Git and CI/CD Experience with workflow orchestration tools such as Airflow, Databricks Workflows or equivalent Proficiency in Apache Airflow, CI/CD and DevOps practices Familiarity with Gen AI in SDLC English proficiency at B2 level or higher Nice to have Familiarity with Anthropic Claude Code

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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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