Principal ML Engineer, Machine Learning Platform – Systems Architecture

🕒 Maio 6

🍂 Massachusetts, Virginia – Remoto

🍂 Massachusetts – Remote ⚔️ Virginia – Remote

💵 $152.000 - $272.250 / ano

⏰ Tempo Integral

🔴 Especialista

⚙️ Engenheiro de Sistemas

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Autodesk

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1982

📱 Mídia

Architecture • Engineering • Media

A Autodesk é líder global em software para designers, engenheiros, construtores e criadores. A empresa oferece um portfólio abrangente de aplicativos de design e engenharia, incluindo produtos populares como AutoCAD, Revit e 3ds Max. Por meio de sua plataforma Design and Make, a Autodesk capacita profissionais de diversos setores a projetar, visualizar e gerenciar projetos com eficiência, fomentando a inovação e a sustentabilidade em arquitetura, engenharia, construção e manufatura.

Descrição

• Lead architecture and delivery for major ML platform capabilities across training, evaluation, deployment, and observability • Design scalable systems for distributed training, data processing, feature and model lifecycle management, and production inference • Own platform-level technical outcomes from design through deployment, operations, and continuous improvement • Drive the design and scaling of data pipelines for large-scale structured and semi-structured technical datasets • Lead architecture for distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms • Establish strong practices for data lineage, provenance, governance, and responsible data usage in ML systems • Guide the design of model deployment, inference services, monitoring, and observability for production ML workloads • Contribute to the development of ML-ready representations for geometry, graph, hierarchical, or multimodal data • Clarify ambiguous problem spaces, define solution approaches, and lead execution across multiple engineers and teams • Establish and improve engineering standards, operational practices, and architectural patterns for ML systems • Lead incident response for critical platform issues and drive lasting improvements across system health and supportability • Mentor engineers and act as a force multiplier through design leadership, coaching, and technical reviews • Communicate technical strategy, tradeoffs, and execution plans clearly to technical and non-technical stakeholders

🎯 Requisitos

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent industry experience • Typically 6 to 8 years of industry experience in software engineering, ML infrastructure, distributed systems, or platform engineering, including experience leading design and delivery of complex technical systems • Deep experience in software architecture, distributed systems, large-scale data platforms, or ML infrastructure • Strong proficiency in Python and strong command of production software engineering practices • Experience leading complex technical initiatives that span multiple engineers or cross-functional teams • Strong experience with large-scale data pipelines, distributed data processing, and cloud-native platform architectures • Experience with model deployment, inference systems, and production observability • Demonstrated ability to make architecture decisions that balance performance, scalability, reliability, and cost • Strong communication and stakeholder management skills

🏖️ Benefícios

• Health and financial benefits • Time away and everyday wellness