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