Autodesk
SeniorPrincipalMachineLearningEngineer,MLPlatformandSystemsArchitecture
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture at Autodesk. Skills: ML Platform, Systems Architecture, Technical Strategy, Distributed Systems. Define and lead technical strategy for machine learning. Drive architecture decisions for scalable training systems”
What You'll Achieve.
Align platform investments with long-term product and business outcomes
Industry & Context.
Resolve complex technical problems; Risk management
What They're Looking For.
Must Have
Bachelor's or Master's degree in Computer Science, Engineering, or related field, or equivalent industry experience, 8+ years of industry experience in software engineering, ML platform architecture, distributed systems, or related domains, Significant experience in software architecture, distributed systems, platform engineering, or ML infrastructure at scale, Deep expertise in distributed training, data platforms, ML platform architecture, model serving, or reliability engineering, Proven record of leading technical strategy and delivering cross-team outcomes, Command of cloud-native architectures, production engineering practices, and large-scale system design, Demonstrated ability to influence architecture and engineering standards beyond a single team, Executive-level communication
Nice to Have
Experience setting architecture direction for ML platforms used across multiple teams or organizations, Experience building or scaling data pipelines for large-scale structured and semi-structured technical datasets, Experience with data lineage, provenance, governance, and responsible data usage in ML systems, Experience with distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms, Experience with model deployment, inference services, monitoring, and observability for production ML systems, Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data, Experience building or scaling foundation model infrastructure and high-throughput data systems, Experience leading engineering improvements around resiliency, service reviews, fire drills, and risk reduction, Familiarity with AEC, design technology, BIM/CAD ecosystems, or Autodesk products, External technical leadership through architecture leadership, speaking, or domain expertise
What You'll Do.
Define and lead technical strategy for machine learning
Drive architecture decisions for scalable training systems
Drive architecture decisions for data systems
Drive architecture decisions for evaluation systems
Drive architecture decisions for deployment systems
Drive architecture decisions for observability systems
Drive architecture decisions for reliability systems
Lead multi-team initiatives with far-reaching technical impact
Define technical direction for data pipelines
Set standards for data lineage
Set standards for data provenance
Set standards for data governance
Set standards for responsible data usage in ML
Lead architecture for distributed data processing systems
Lead architecture for orchestration systems
Define scalable approaches for model deployment
Define scalable approaches for inference services
Define scalable approaches for monitoring
Define scalable approaches for observability for production ML
Influence platform direction for ML-ready representations of geometry
Influence platform direction for ML-ready representations of graph
Influence platform direction for ML-ready representations of hierarchical
Influence platform direction for ML-ready representations of multimodal
Influence standards for engineering quality
Influence standards for architecture
Influence standards for resiliency
Influence standards for risk management
Influence standards for operational excellence
Identify long-term technical and operational risks
Guide investment decisions that future-proof platform capabilities
Serve as a technical authority and trusted advisor
Resolve complex cross-team technical problems
Champion engineering practices that improve service quality
Champion engineering practices that improve release readiness
Champion engineering practices that improve monitoring
Champion engineering practices that improve incident response
Champion engineering practices that improve maintainability
Mentor senior engineers
Help build the next level of technical leadership
Clearly articulate the business rationale for technical investments
Ensure alignment with broader organizational goals
How You'll Work.
Team & Collaboration
Across organizational boundaries; Cross-functional stakeholders; Engineering leaders; Senior engineers
Communication Scope
Executive-level communication; Articulate business rationale
Full Job Description
**Job Requisition ID #** 26WD94803 ## **Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture** ## ## **Position Overview** The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world to solve problems that matter. Autodesk is seeking a **Senior Principal ML Engineer, ML Platform and Systems Architecture** to define and drive the technical strategy for large-scale machine learning platforms and systems. This is a top-level engineering leadership role for a technical authority who can shape multi-year architecture, influence engineering standards across teams, and lead major platform initiatives that connect research, product, and business goals. You will be responsible for driving the evolution of the systems that enable machine learning across Autodesk, including training infrastructure, data platforms, evaluation and experimentation systems, model serving frameworks, and operational excellence for production ML. You will work across organizational boundaries to guide decisions, resolve hard technical challenges, and ensure that platform investments are aligned with long-term product and business outcomes. This role is fully remote-friendly, with team members distributed across the US and Canada. **Location: US or Canada Remote** ## ## **Responsibilities** * Define and lead technical strategy for a domain or large-scale platform supporting machine learning systems * Drive architecture decisions across teams for scalable training, data, evaluation, deployment, observability, and reliability systems * Lead multi-team initiatives with far-reaching technical impact across a function, platform, or division * Define technical direction for data pipelines that support large-scale structured and semi-structured technical datasets * Set standards for data lineage, provenance, govern
Applying for this Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Workday
- Workday has a multi-step form — save your progress after every section.
- "Apply With LinkedIn" can fail or lose data; manual entry is more reliable.
- Watch for the "Submit for Review" final step — hitting "Save" alone does not submit.
- Job requisition numbers are useful when following up with HR by email.
ANONYMOUS · UNFILTERED
What do employees actually say about Autodesk?
Real rants from real employees. Read before you apply.