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Core & ML Ops Team Lead - Remote

16 hours, 48 minutes ago
Hungary, Poland, Portugal, Spain, Brazil
Full-time
Lead
Machine Learning Engineer
DevOps and Infrastructure
Apache Airflow C++ CI/CD Docker Go Java Kafka Kubernetes Linux Mesos Microservices Python REST API Rust TCP/IP
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Zyte

Zyte

Zyte is a leading provider of Full Stack Web Scraping API and World Class Data Extraction Services. With AI-powered web scraping platform, Zyte offers fast and reliable data extraction solutions for over 2,000 companies and 1 million developers worldwi...

Professional Services
251-1K
Founded 2010
$3M raised
View All Jobs 5

Description

  • Design and evolve the core platform infrastructure (container orchestration, GPU scheduling/autoscaling, and distributed compute).
  • Own the model platform including registry, experiment tracking, training orchestration, evaluation, serving, and monitoring.
  • Build and maintain the Golden Path: reference repositories, scaffold CLI, opinionated CI/CD pipelines, runtime contracts (health/metrics/tracing/SLOs), and production-ready defaults.
  • Operate a secure, multi-tenant model registry and training platform with standardized experiment/evaluation harnesses.
  • Provide turnkey serving patterns for online and batch inference, including drift/quality monitoring and rollback playbooks.
  • Integrate public and open-source AI capabilities as managed platform services with cost and data-governance guardrails.
  • Run the squad: set roadmap and priorities, drive delivery, mentor engineers, and uphold high engineering standards and platform-thinking.
  • Partner with product engineering, Prod Ops, and Security on adoption, rollout plans, observability, billing/cost tracking, and supply-chain security.

Requirements

  • 5+ years experience building distributed systems and 3+ years in MLOps/ML platform engineering (or equivalent impact).
  • Proven track record designing and operating model platforms in production (registry, training, serving, monitoring).
  • Deep understanding of Linux/OS internals (process model, cgroups/namespaces), networking (TCP/IP, HTTP/2), concurrency, and performance profiling.
  • Strong knowledge of Kubernetes (Mesos experience a bonus) and GPU infrastructure provisioning, scheduling, containerization, and optimization.
  • Proficiency developing high-performance services in Java, Rust, Go, or C++ (bonus: vert.x/Netty); strong Python skills.
  • Demonstrated success leading technical teams and implementing organization-wide platform solutions.
  • Experience with observability and reliability practices (logging/metrics/tracing pipelines, SLIs/SLOs, incident management) and cost governance for ML/AI workloads.
  • Familiarity with streaming and workflow tools (Kafka, Argo, Temporal, Airflow) and experience with multi-tenant quotas/fairness.
  • Hands-on experience authoring Golden Paths (service templates, CI/CD blueprints, CLI scaffolds) and supply-chain security practices (SBOM, image signing).
  • Preferred experience with eBPF-based observability, perf tooling or io_uring, and cost-optimization strategies for ML workloads.

Benefits

  • Completely remote company with the freedom and flexibility to work from where you do your best work.
  • Be part of a self-motivated, progressive, multi-cultural team that fosters and nourishes new ideas.
  • Opportunity to work with cutting-edge open-source technologies and tools.
  • Support for bringing new ideas to market and a culture focused on innovation.

Interested in this position?

Apply directly on the company website

Apply Now

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