Senior MLOps, Data Systems Engineer

🕒 Maio 11

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $176.000 - $242.000 / ano

⏰ Tempo Integral

🟠 Sênior

⚙️ Engenheiro de Sistemas

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Lime

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

Fundada em 2017

🚗 Transporte

🛍️ Comércio Eletrônico

☁️ SaaS

💰 $418.000.000 Convertible Note em 2021-11

Transport • eCommerce • SaaS

A Lime é uma empresa de transporte que oferece patinetes e bicicletas elétricas para mobilidade urbana. Através de seu aplicativo amigável, os clientes podem localizar, desbloquear e andar facilmente em patinetes e bicicletas elétricas para viagens convenientes dentro das cidades. A Lime enfatiza segurança, sustentabilidade e engajamento comunitário, posicionando-se como uma escolha responsável para opções de deslocamento ecologicamente corretas.

Descrição

• ML Pipeline & Data Systems Development: Design, build, and maintain scalable pipelines that span data ingestion, annotation, validation, training, evaluation, and deployment, ensuring reproducibility, consistency, and traceability across the full ML lifecycle. • Data & Annotation Pipeline Integration: Build and integrate annotation workflows with upstream data ingestion and training systems, enabling efficient task creation, labeling, QA, and dataset updates that directly support model iteration. • Data-Centric Iteration: Analyze model performance and failures, and drive targeted data improvements by connecting production signals, data mining, and annotation workflows into continuous feedback loops. • Experimentation & Reproducibility: Implement systems for experiment tracking, dataset versioning, and model lineage to enable reliable comparison and iteration across experiments. • CI/CD for Machine Learning: Develop and maintain CI/CD workflows tailored to ML systems, enabling automated testing, validation, and deployment of models and pipelines. • Model Deployment Support: Collaborate with embedded and platform teams to support the deployment of models to edge environments, ensuring compatibility, performance, and reliability. • Monitoring & Feedback Loops: Implement monitoring, logging, and feedback systems to track model performance in production and drive continuous improvement through data and model iteration. • Compute Optimization: Optimize training and inference workflows across cloud environments, including efficient utilization of GPU and compute resources. • Cross-Functional Collaboration: Work closely with applied scientists, embedded engineers, and data teams to ensure alignment across data workflows, model development, and deployment systems. • End-to-End Contribution: Participate in and improve the full ML lifecycle, from raw data ingestion and annotation through training, evaluation, deployment support, and post-deployment analysis.

🎯 Requisitos

• 5+ years of industry experience in MLOps, ML infrastructure, data systems, Machine Learning Engineering, or related roles. • Strong programming skills in Python, with experience in ML frameworks such as PyTorch or TensorFlow. • Experience building and maintaining end-to-end ML pipelines, including data ingestion, annotation, training, evaluation, and deployment workflows. • Experience designing or integrating annotation and data curation workflows, and understanding how labeled data impacts model performance. • Strong understanding of dataset versioning, data lineage, and reproducibility in machine learning systems. • Experience with experiment tracking and model lifecycle management. • Familiarity with CI/CD tools (e.g., GitHub Actions, GitLab CI, Jenkins) and applying them to machine learning workflows. • Experience with containerization (Docker) and workflow orchestration systems. • Experience with cloud-based ML environments (e.g., AWS) and distributed training workflows. • Strong understanding of real-world data challenges, including noisy inputs, edge cases, and variability across environments. • Strong problem-solving and debugging skills, particularly in complex, multi-stage systems. • Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field (or equivalent practical experience).

🏖️ Benefícios

• Comprehensive Health & Wellness: A choice of medical, dental, and vision plans. We also provide company-paid life and disability insurance and company-funded mental health benefits. • Financial & Retirement Planning: 401(k) plan with both pre-tax and Roth options, and access to a Health Savings Account (HSA) with a monthly company contribution. • Family & Fertility Support: Paid parental leave for birthing and non-birthing parents, plus fertility and family-forming benefits. • Paid Time Off: Unlimited vacation, paid leaves, and 10 company holidays. • Unique Lime Perks: Complimentary use of Lime vehicles in participating cities, a monthly phone allowance, dedicated learning and development days, and access to perks including One Medical, Wellhub, and Headspace.