Summary
Join a global engineering team to operate and improve large-scale machine learning infrastructure in production. Build cloud platforms, automate operations, support GPU environments, and collaborate with researchers to deliver reliable AI services.
Highlights
Fully remote role with ownership of production ML infrastructure, international collaboration, extensive learning resources, relocation opportunities, and comprehensive employee benefits.
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.
This is a fully remote position that offers you the flexibility to work from any location in Armenia, whether it's your home or well-equipped offices in Yerevan or Gyumri.
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 rotationBuild and improve AWS infrastructure, including infrastructure as code, CI/CD pipelines, Kubernetes, Docker, autoscaling, monitoring, load testing and cost controlCare for the GPU fleet through NVIDIA driver and CUDA upgrades, node provisioning and debugging, and capacity managementAutomate user access, including SSH credentials, service accounts and developer environments for the science teamRun real-time production data pipelines, including streaming ingestion into an online feature store and serving features to low-latency endpointsOrchestrate batch jobs with Airflow or Databricks WorkflowsPartner with applied scientists to productionize their prototypes and keep them healthyWrite 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 liveStrong Linux systems skills, with hands-on experience in Kubernetes, Docker and infrastructure as codeSolid experience in Python, Git and CI/CDExperience with workflow orchestration tools such as Airflow, Databricks Workflows or equivalentProficiency in Apache Airflow, CI/CD and DevOps practicesFamiliarity with Gen AI in SDLCEnglish proficiency at B2 level or higher
Nice to have
Familiarity with Anthropic Claude Code
We offer
We connect like-minded peopleDelivering innovative solutions to industry leaders, making a global impactEnjoyable working environment, whether it is the vibrant office or the comfort of your homeOpportunity to work abroad for up to two months per yearRelocation opportunities within our offices in 55+ countriesCorporate and social eventsWe invest in your growthLeadership development, career advising, soft skills and well-being programsCertifications, including GCP, Azure and AWSUnlimited access to EPAM's internal learning databaseFree English classes with certified teachersWe cover it allParticipation in the Employee Stock Purchase PlanMonetary bonuses for engaging in the referral programComprehensive medical & family care packageFour trust days per year for personal needsDiscounts for fitness clubsBenefits package (hotels, restaurants, stores and services)
EPAM Armenia is a team of talented innovators united by a passion for technology.
In 2014, we opened our first office in Yerevan, and now we have a second engineering hub in Gyumri.
We've built a continuously learning organization that helps its employees rapidly advance their careers.
Here you will work with the world's industry leaders, support impactful projects using the latest technologies, collaborate with multi-national teams, and have access to a wide variety of development opportunities.
