Staff AI/ML Platform Engineer

Emploi pas sur LinkedIn

🕒 il y a 6 mois

🏄 California – Distant

🏄 California – Remote

⏰ Temps Plein

🔴 Expert

🏗️ Ingénieur Plateforme

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Albert Invent

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2022

🤖 Intelligence artificielle

🧬 Biotechnologie

🔬 Science

💰 Seed Round en 2023-06

Artificial Intelligence • Biotechnology • Science

Albert Invent est une plateforme de bout en bout qui numérise la synthèse, la formulation et la science des matériaux à l'ère de l'IA. Elle combine des capacités telles que la gestion des stocks, les cahiers de laboratoire électroniques (ELN), les systèmes de gestion des informations de laboratoire (LIMS) et l'intelligence réglementaire pour rationaliser les processus de recherche et développement. Reconnue par des milliers de chimistes dans 36 pays, Albert Invent améliore la productivité et accélère l'innovation en recherche chimique grâce à l'utilisation des technologies avancées d'IA et d'apprentissage automatique.

Description

• You'll own the APIs, data pipelines, and workflow orchestration that power our AI products—from real-time model inference to long-running optimization pipelines. • This role sits at the intersection of backend engineering and data engineering: you'll build the services that serve up models, manage workflows, and connect AI capabilities to the structured data that makes them useful. • You'll work closely with our Active Learning and LLM/Agents team leads, translating their product vision into scalable, production-grade systems. • The infrastructure you build will power model playgrounds for chemists, inverse design pipelines that optimize experiments across high-dimensional spaces, and orchestrated agent workflows that reason through complex scientific problems. • Design and build high-performance Python APIs that serve models, manage workflows, and expose AI capabilities to the broader platform • Architect backend services for scalability, reliability, and low latency • Build integrations between AI/ML systems, graph databases, and external data sources • Build and maintain long-running workflow pipelines using Ray and Temporal. • Design orchestration patterns for multi-step agent pipelines, batch inference, and numerical optimization workflows • Ensure fault tolerance, graceful degradation, and efficient resource utilization. • Architect and maintain data pipelines that feed AI/ML workflows • Work with Neptune (graph), Redis, DynamoDB, and other data stores to enable efficient data access patterns • Implement observability including logging, metrics, tracing, and alerting • Own system reliability—troubleshoot issues, conduct post-mortems, and continuously improve. • Design CI/CD pipelines and promote automation best practices.

🎯 Exigences

• Deep expertise in Python backend development and building production APIs • Experience designing and operating data pipelines and workflow orchestration systems • A builder's mindset—you want to create foundational systems that others build on • Genuine curiosity about how your work enables scientific discovery • A commitment to rigor: AI makes mistakes confidently, and our customers won't accept hand-waving—neither should we • A degree in Computer Science or a related field with 7+ years of industry experience (Bachelor's) or 5+ years (Master's or PhD) in software engineering • Advanced proficiency in Python including async programming and performance optimization • Experience building and maintaining REST APIs using FastAPI or similar frameworks • Experience with workflow orchestration tools (Ray, Temporal, or similar) • Strong background in data engineering: pipelines, transformations, and working with diverse data stores • Experience with cloud platforms (AWS preferred) and containerization (Docker, Kubernetes) • Familiarity with graph databases, key-value stores, or other NoSQL systems (Neptune, Redis, DynamoDB a plus) • Track record of operating production systems at scale.

🏖️ Avantages

• We care about you. • We love distributed teams. • We value diversity.