[Hiring] Principal Applied AI Developer, Foundation Models Infrastructure @Autodesk

Role Description

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, products, infrastructure, and entertainment, we empower some of the most creative people in the world.

Autodesk is building cloud-scale software, data platforms, and AI-enabled capabilities that help customers design, build, and operate the world around them. As a Principal Applied AI Developer on the Foundation Model ML Infrastructure team, you will help define and accelerate the roadmap for the Autodesk Machine Learning Platform, the platform used by Autodesk researchers, ML developers, and product teams to support the full lifecycle of Autodesk’s machine learning models.

You will design, build, and evolve resilient, secure, scalable, observable, and cost-effective platform services that support model training, inference, evaluation, deployment, and serving at global scale. You will work closely with researchers, ML developers, product teams, security, privacy, and platform partners to translate ambiguous business and technical requirements into robust platform capabilities with excellent developer experience and strong self-service workflows.

This is a principal-level technical leadership role for someone who combines deep hands-on engineering expertise with the ability to define technical direction, lead complex initiatives across teams, mentor senior developers, and raise the bar for engineering excellence.

Responsibilities

• Define and drive technical strategy for Foundation Model ML Infrastructure capabilities within the Autodesk Machine Learning Platform.
• Lead the design and implementation of large-scale platform services that support the full lifecycle of Autodesk’s ML models, including training, inference, serving, evaluation, deployment, monitoring, and operations.
• Architect highly resilient, secure, observable, scalable, and cost-effective infrastructure for large-scale AI and ML workloads.
• Build and evolve developer-facing APIs, tools, workflows, and self-service capabilities that enable researchers and ML developers to move quickly and safely.
• Work hands-on with Kubernetes, Ray, SageMaker, AWS, and related cloud-native technologies to support distributed training, scalable inference, and production model serving.
• Identify, frame, and prioritize high-impact technical problems aligned with product, research, and platform strategy.
• Translate ambiguous AI research goals, product needs, and business requirements into practical technical designs and executable engineering plans.
• Lead complex cross-team technical initiatives, align stakeholders, and influence technical direction without requiring direct authority.
• Drive reliability, scalability, performance, security, quality, and cost improvements across training, inference, and serving workloads.
• Establish and evolve platform standards for production readiness, observability, SLAs/SLOs, incident response, release quality, model deployment, versioning, lineage, and governance.
• Partner with researchers, ML developers, product managers, architects, security, privacy, and platform teams to define quality bars and safe production deployment practices, including Trusted AI requirements.
• Improve developer productivity through CI/CD, automated testing, infrastructure as code, contract testing, quality gates, documentation, and platform automation.
• Lead root-cause analysis for systemic production issues and implement durable, platform-level improvements.
• Act as a technical authority for critical decisions, guiding trade-offs across performance, reliability, security, cost, scalability, and developer experience.
• Mentor senior developers, elevate engineering standards, and foster a culture of ownership, quality, action, and accountability.
• Actively participate in Agile, Kanban, or other modern development methodologies to deliver high-quality outcomes incrementally.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Machine Learning, or equivalent practical experience.
• 8+ years of professional software engineering experience, including significant experience with large-scale, cloud-native, distributed, platform, or machine learning infrastructure systems.
• Experience using AI-assisted development tools, coding agents, and AI-powered automation to improve engineering productivity.
• Deep hands-on experience designing, building, and operating production-grade services that support model training, inference, serving, evaluation, deployment, or observability.
• Strong experience with Kubernetes and cloud-native infrastructure.
• Experience with distributed compute, ML infrastructure, or model serving technologies such as Ray, SageMaker, distributed training platforms, inference serving platforms, or equivalent systems.
• Proven ability to lead complex technical initiatives across teams and influence technical direction without direct authority.
• Experience translating ambiguous research, product, or business requirements into practical technical designs and executable engineering plans.
• Strong experience designing and operating resilient, secure, observable, and cost-effective production systems using CI/CD, automated testing, infrastructure as code, monitoring, alerting, and production operations practices.
• Demonstrated ability to mentor developers, elevate engineering standards, and act as a strong technical voice for excellence.
• Strong written and verbal communication skills, with the ability to influence technical and non-technical stakeholders.

Preferred Qualifications

• Experience with advanced AI-assisted development patterns such as harness engineering, coding-agent orchestration, skills, MCPs, prompt/context design, evaluation loops, and reusable AI-enabled engineering workflows.
• Experience building or evolving internal developer platforms, ML platforms, self-service infrastructure, or platform APIs used by researchers and ML developers.
• Experience supporting large-scale model training, fine-tuning, batch inference, real-time inference, model serving, or foundation model workflows.
• Experience defining platform architecture, technical strategy, service boundaries, reliability standards, production readiness criteria, and operational practices.
• Experience designing systems with clear SLAs or SLOs for latency, throughput, availability, reliability, and cost.
• Familiarity with model governance, model versioning, lineage, evaluation workflows, Trusted AI, security, privacy, and responsible AI practices.
• Track record of leading cross-team technical initiatives, raising engineering quality, and improving developer productivity.
• Experience working with AI research teams, ML developers, product teams, and platform organizations to productionize applied AI capabilities.

The Ideal Candidate

You are a highly experienced developer who combines deep technical expertise with the ability to define direction, drive alignment, and deliver impact across teams. You are comfortable operating in ambiguity, framing the right technical problems, and leading complex initiatives from concept to production.

You think in terms of systems, platforms, and developer experience, not just individual services or features. You understand how to design scalable, secure, reliable, and cost-effective infrastructure that enables researchers and ML developers to build, train, deploy, and operate machine learning models safely at scale.

You have a strong bias toward action and make thoughtful technical tradeoffs quickly. You balance short-term delivery with long-term platform health. You communicate clearly, build trust with partners, and help teams make better technical decisions.

You are pragmatic, curious, collaborative, and passionate about solving complex infrastructure problems in service of Autodesk’s researchers, ML developers, product teams, and global customers.

Salary Transparency

Salary is one part of Autodesk’s competitive compensation package. For Canada based roles, we expect a starting base salary between $153,000 and $224,400. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Company Description

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!