Core & ML Ops Team Lead - Remote

5+ years experience building distributed systems 3+ years in MLOps/ML platform engineering (or equivalent impact) Knowledge of Linux/OS internals, networking, concurrency, and performance profiling Deep understanding of Kubernetes (bonus: Mesos) Proficiency developing high-performance services in Java, Rust, Go or C++ (bonus: familiarity with vert.x and Netty frameworks) Strong Python skills Experience with GPU infrastructure (scheduling, containerization, optimization) Track record of designing and operating model platforms (registry, training, serving, monitoring) in production Demonstrated success leading technical teams and implementing organization-wide platform solutions Preferred: Streaming & workflows (Kafka, Argo/Temporal/Airflow) Preferred: eBPF-based observability, perf tooling, or io_uring experience Preferred: Cost optimization for ML/AI; multi-tenant quotas and fairness Preferred: Hands-on experience authoring Golden Paths Preferred: SRE practices (SLIs/SLOs, incident management)

Design and evolve the core platform (Kubernetes, Mesos, GPU scheduling/autoscaling, distributed compute) Own the model platform: registry, experiment tracking, training orchestration, evaluation, serving, and monitoring Build the Golden Path: reference repos, scaffold CLI, CI/CD pipelines, runtime contracts, high-performance clients Operate a secure, multi-tenant model registry and training platform Provide turnkey serving patterns (online + batch), drift/quality monitoring, and rollback playbooks Integrate public/open-source AI capabilities as managed platform services Run the squad: roadmap/prioritization, delivery, mentoring, and high engineering standards Partner with product engineering, Prod Ops, and Security on adoption and rollout plans Mentor the team and foster a platform-thinking mindset