Senior MLOps, Data Systems Engineer

🕒 vor 28 Tagen

🇺🇸 Vereinigte Staaten – Remote

💵 $176.000 - $242.000 / Jahr

⏰ Vollzeit

🟠 Senior

⚙️ Systemingenieur

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

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Lime

WebsiteLinkedInAlle Stellen

501 - 1000 Mitarbeiter

Gegründet 2017

🚗 Transport

🛍️ eCommerce

☁️ SaaS

💰 €418.000.000 Convertible Note im 2021-11

Transport • eCommerce • SaaS

Lime ist ein Transportunternehmen, das Elektroscooter und Fahrräder für urbane Mobilität bereitstellt. Über seine benutzerfreundliche App können Kunden E-Scooter und E-Bikes problemlos lokalisieren, entsperren und für bequeme Fahrten innerhalb der Städte nutzen. Lime legt großen Wert auf Sicherheit, Nachhaltigkeit und gesellschaftliches Engagement und positioniert sich als verantwortungsvolle Wahl für umweltfreundliche Pendeloptionen.

Beschreibung

• 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.

🎯 Anforderungen

• 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).

🏖️ Vorteile

• 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.