MLOps, ML Platform Engineer

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🕒 Fevereiro 26

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SumerSports

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2022

⚽ Esportes

🤖 Inteligência Artificial

☁️ SaaS

Sports • Artificial Intelligence • SaaS

A SumerSports é uma empresa de tecnologia e análises esportivas impulsionada por IA, focada em futebol americano (NFL e NCAA). Combinando mais de 500 anos de experiência na NFL com aprendizado de máquina, a SumerSports oferece produtos como o SūmerBrain para recuperação de filmes e dados multilayer, o SūmerLive para acompanhamento de jogos, SūmerNFL e SūmerNCAA para construção de elenco e otimização de times, e uma plataforma de métricas verificadas por jogadores e exposição de talentos. A empresa produz guias de drafts, conteúdo analítico com ex-olheiros e membros do Hall da Fama, além de ferramentas que atendem jogadores, equipes e fãs para melhorar a avaliação de scouting, decisões de elenco e desempenho.

Descrição

• 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 • Serve models in production: Operate APIs for low-latency inference with autoscaling, blue-green or canary rollouts, and rollback safety • 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

🎯 Requisitos

• 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) • Hands-on experience managing GPU clusters and training/inference pipelines • Familiarity with data orchestration and storage formats (Delta, Parquet, Polars, Spark) • Proven ability to ship and operate production ML systems with SLOs • Strong Python skills and comfort with infrastructure as code and automation • Experience with observability and cost optimization at scale

🏖️ Benefícios

• Competitive Salary and Bonus Plan • Comprehensive health insurance plan • Retirement savings plan (401k) with company match • Remote working environment • A flexible, unlimited time off policy • Generous paid holiday schedule - 13 in total including Monday after the Super Bowl