{"id":786051,"url":"https://alion.io/job/sumersports-mlops-ml-platform-engineer","title":"MLOps / ML Platform Engineer","company":{"id":688645,"name":"SumerSports","domain":"sumersports.com","url":"https://alion.io/company/sumersports","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US","CA"],"hiring_countries_total":2,"salary":null,"salary_estimate":{"min_usd":109000,"max_usd":216000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":85},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Blue-Green Deployment","optional":false},{"name":"CI/CD","optional":false},{"name":"GCP","optional":false},{"name":"IAM","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Polars","optional":false},{"name":"Python","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Spark","optional":false},{"name":"gRPC","optional":true},{"name":"LLM","optional":true},{"name":"Rest API","optional":true}],"status":"live","first_seen_at":"2026-09-10T23:13:02Z","employer_posted_date":"2026-09-10","last_verified_at":"2026-10-29T11:53:26Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"description":"SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia.\nOur 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.\nWhat 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. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football.\nResponsibilities\nDesign and operate ML infrastructure: Manage data, training, serving, and inference systems for high-throughput model workflows.\nBuild scalable pipelines: Implement reproducible training and evaluation pipelines with versioning, scheduling, and artifact tracking.\nOptimize compute and cost: Tune GPU and CPU workloads, manage clusters, and drive efficiency via rightsizing, spot scheduling, and caching.\nServe models in production: Operate APIs for low-latency inference with autoscaling, blue-green or canary rollouts, and rollback safety.\nEnsure reliability and observability: Define and own SLOs; instrument pipelines and services to track latency, cost, drift, and data quality.\nSecure and automate: Manage IAM, secrets, and container security; automate deployment pipelines via CI/CD and infrastructure as code.\nCollaborate cross-functionally: Partner with research scientists and AI engineers to deliver models from experiment to production with minimal friction.\nDocument and enable: Build templates, runbooks, and internal tooling that make ML workflows repeatable, safe, and fast.\nQualifications\n4+ years of experience in ML platform, DevOps, or infrastructure engineering.\nDeep knowledge of Kubernetes, CI/CD, containers, and cloud infrastructure (AWS, GCP, or Azure).\nHands-on experience managing GPU clusters and training/inference pipelines.\nFamiliarity with data orchestration and storage formats (Delta, Parquet, Polars, Spark).\nProven ability to ship and operate production ML systems with SLOs.\nStrong Python skills and comfort with infrastructure as code and automation.\nExperience with observability and cost optimization at scale.\nNice to Have\nExperience with real-time or low-latency model serving (REST, gRPC).\nExposure to model registry and promotion workflows.\nFamiliarity with data quality, lineage, and curation pipelines.\nBackground in sports analytics or other high-volume data domains.\nExperience integrating LLM workflows or evaluation pipelines.\nBenefits\nCompetitive Salary and Bonus Plan\nComprehensive health insurance plan\nRetirement savings plan (401k) with company match\nRemote working environment\nA flexible, unlimited time off policy\nGenerous paid holiday schedule - 13 in total including Monday after the Super Bowl\nSumerSports is committed to fair and equitable compensation practices.\nActual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. 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