SumerSports

SumerSports

MLOps / ML Platform Engineer

Remote (United States)

Sponsorship not specifiedDetected 274 days ago
PythonDistributed SystemsAWSGCPAzureCloud PlatformsKubernetesCI/CDDevOpsPlatform EngineeringRESTgRPCMachine LearningDeep LearningSparkLLMsLLMOpsMLOpsResearch

About the role

  • SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs.
  • What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience.
  • This is a hands-on engineering role that blends software infrastructure, distributed systems, and machine learning productionization.

Responsibilities

  • Design and operate ML infrastructure: Manage data, training, serving, and inference systems for high-throughput model workflows.
  • Build scalable pipelines: Implement reproducible training and evaluation pipelines with versioning, scheduling, and artifact tracking.
  • Optimize compute and cost: Tune GPU and CPU workloads, manage clusters, and drive efficiency via rightsizing, spot scheduling, and caching.
  • Ensure reliability and observability: Define and own SLOs; instrument pipelines and services to track latency, cost, drift, and data quality.
  • Secure and automate: Manage IAM, secrets, and container security; automate deployment pipelines via CI/CD and infrastructure as code.
  • Collaborate cross-functionally: Partner with research scientists and AI engineers to deliver models from experiment to production with minimal friction.
  • Document and enable: Build templates, runbooks, and internal tooling that make ML workflows repeatable, safe, and fast.
  • Design and operate
  • Manage data, training, serving, and inference systems for high-throughput model workflows.
  • Implement reproducible training and evaluation pipelines with versioning, scheduling, and artifact tracking.

Requirements

  • 4+ years of experience in ML platform, DevOps, or infrastructure engineering.
  • Deep knowledge of Kubernetes, CI/CD, containers, and cloud infrastructure (AWS, GCP, or Azure).
  • Familiarity with data orchestration and storage formats (Delta, Parquet, Polars, Spark).
  • Proven ability to ship and operate production ML systems with SLOs.
  • Experience with observability and cost optimization at scale.

Nice to have

  • Experience with real-time or low-latency model serving (REST, gRPC).
  • Exposure to model registry and promotion workflows.
  • Familiarity with data quality, lineage, and curation pipelines.
  • Background in sports analytics or other high-volume data domains.
  • Experience integrating LLM workflows or evaluation pipelines.

Skills

  • Our data-driven platform empowers teams with insights and tools to make informed decisions within salary cap constraints.
  • The platform also serves the NCAA, offering insights around the transfer portal and more.

This listing is sourced directly from SumerSports's careers page and normalized into a canonical job model.