Autodesk
PrincipalAppliedAI/MLEngineer
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“Principal Applied AI/ML Engineer at Autodesk. Skills: Applied AI, ML systems, Software engineering, Cloud infrastructure. Lead architecture, design, and evolution of production-grade applied. Own complex technical problems across the stack”
What You'll Achieve.
Turn ambiguous opportunities into durable technical outcomes; Measurable outcomes
Industry & Context.
Solving the hardest cross-functional problems; Simplify; Prioritize; Make sound tradeoff decisions
What They're Looking For.
Must Have
Deep experience building and scaling production software systems with meaningful AI/ML components, Python mastery, Fluent with latest AI/ML research and implementations/patterns, Proven success leading architecture and delivery for complex, cross-functional technical initiatives, Hands-on engineering ability in backend systems, APIs, services, data pipelines, and production operations, Significant experience with AWS administration and optimization, Understanding of database systems design and optimization, especially relational systems, Ability to work effectively as a technical generalist across adjacent areas including DevOps, infrastructure engineering, quality/QA, and delivery planning, Excellent judgment in ambiguous situations, Outstanding written communication, Outstanding verbal communication, Demonstrated success collaborating across geographies, functions, and time zones
Nice to Have
Graph database experience strongly preferred
What You'll Do.
and evolution of production-grade applied
Own complex technical problems across the stack
Set technical direction for AI solutions
Drive platform and systems decisions across AWS environments
Shape design and optimization of data systems
Lead infrastructure thinking for distributed and cross-regional services
Establish stronger engineering quality practices
Translate ambiguous business or product opportunities into technical
Partner across engineering
Provide technical leadership across a team
Raise the bar for execution
Create structure in ambiguous environments
Ensure follow-through across distributed teams
How You'll Work.
Team & Collaboration
Across geographies; Across functions; Across time zones; Across disciplines; Across engineering, product, data science, analytics, and business stakeholders
Communication Scope
Written communication; Verbal communication; Technical strategy memos; Design reviews; Decision records; Async execution updates
Process & Methodology
Project planning, Tracking dependencies, Defining milestones
Full Job Description
**Job Requisition ID #** 26WD99166 **Position Overview** We are hiring a Principal Applied AI/ML Engineer to lead the design and delivery of high-impact AI systems for Construction AI group, for product, platform, and services for all of Autodesk’s Forma Construction Cloud. This is a senior technical leadership role for someone who is exceptionally self-directed, highly credible across disciplines, and able to turn ambiguous opportunities into durable technical outcomes. This person will operate as a hands-on technical leader across applied AI, software engineering, cloud infrastructure, data systems, and delivery execution. They should be capable of going deep on architecture and implementation when needed, but their real leverage comes from defining direction, solving the hardest cross-functional problems, and raising the effectiveness of the broader team. This role requires a generalist mindset. The right candidate is comfortable moving across AI systems, backend services, AWS infrastructure, administration and optimization, database modeling and performance, cross-regional infrastructure, quality and QA practices, and project planning/tracking. They are not limited by rigid functional boundaries and are willing to step into whatever the team most needs to succeed. The role is based in Canada and will work closely across multiple time zones, especially with teams in India. Exceptional written and verbal communication is essential. **Responsibilites** * Lead the architecture, design, and evolution of production-grade applied AI systems, including LLM, ML, retrieval, agentic, and automation-based capabilities * Own the most complex technical problems across the stack, from model behavior and system design through infrastructure, reliability, quality, and operational scale * Set technical direction for how AI solutions are built, integrated, evaluated, secured, monitored, and improved over time * Drive platform and systems decisions across AWS environments, includin
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