Staff Software Engineer, MDLC

🕒 il y a 2 mois

🇺🇸 États-Unis – Télétravail

💵 $200 000 - $250 000 / an

⏰ Temps Plein

🔴 Expert

🧑‍💻 Développeur Full-Stack

🦅 Parrain de Visa H1B

info

🗣️🇺🇸🇬🇧 Anglais requis

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Logo of Domino Data Lab

Domino Data Lab

201 - 500 employés

Fondée en 2013

🤖 Intelligence artificielle

🏢 Entreprise

☁️ SaaS

💰 Series F en 2022-06

Artificial Intelligence • Enterprise • SaaS

Domino Data Lab est une entreprise qui permet aux entreprises pilotées par l'IA de concevoir et de gérer l'intelligence artificielle à grande échelle grâce à sa plateforme Enterprise AI. La plateforme offre une expérience intégrée pour le développement de modèles, MLOps, la collaboration et la gouvernance, permettant aux entreprises mondiales d'innover dans divers secteurs. Domino soutient un meilleur développement médicinal, une agriculture productive et la création de produits compétitifs. Créée en 2013 et soutenue par des investisseurs renommés tels que Sequoia Capital et NVIDIA, Domino permet aux entreprises d'optimiser efficacement le déploiement de l'IA.

Description

• Integrate model monitoring to provide a holistic view of deployment health and performance • Enhance tagging capabilities across Domino entities to improve discoverability and tracking • Expand LLM hosting capabilities to address customer needs for scale, performance, and logging • Innovate within our Domino Apps offering by incorporating feature requests from major customers

🎯 Exigences

• Building Scalable Systems: Hands-on experience developing and managing high-performance back-end systems in distributed computing environments • Collaboration Across Teams: Working closely with cross-functional teams to integrate systems with front-end interfaces and third-party services • API Development: Designing and implementing secure, scalable APIs (e.g., RESTful APIs, gRPC) • Performance Optimization: Profiling and optimizing back-end performance, especially in cloud environments or with container technologies like Docker and Kubernetes. • Testing and CI/CD: Using robust testing frameworks (unit, integration, end-to-end) and setting up CI/CD pipelines • ML Model Deployment: Familiarity with model registries, versioning, and lifecycle management tools like MLflow or KubeFlow is a big plus • Distributed Computing: Experience with frameworks like Apache Spark, Azure ML, or SageMaker is a plus • Cloud Platforms: Proficiency with cloud providers (AWS, Azure, GCP) and deploying services in these environments • Back-End Development: Expertise in languages such as Python, Java, Scala, or Go

🏖️ Avantages

• equity • company bonus • 401(k) plan • medical, dental, and vision benefits • wellness stipends

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