Autodesk

Technology

SeniorMachineLearningTestEngineer

$155–215k ~AI est. United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Machine Learning Test Engineer at Autodesk. Skills: Machine Learning Test, MLOps, Quality Assurance, Software Engineering. Define ML quality strategy. Define acceptance criteria”

Industry & Context.

Technology
Problems you'll solve

Problem-solving; Root cause analysis; Troubleshooting

What They're Looking For.

Must Have

7+ years software engineering or QA, Python programming skills, Test automation experience, CAD environments tooling familiarity, Automation and UAT framework proficiency, QA frameworks design experience, Excellent problem-solving skills, Attention to detail, Communication skills, Collaboration skills, Software architecture understanding, Agile development environment experience

Nice to Have

Data validation tooling experience, Labeling workflows experience, ML frameworks familiarity, CI/CD tools and processes experience, Data pipelines experience, Orchestration tools experience, MLOps practices experience, ML evaluation methods experience, Metrics and benchmarking experience, Cloud providers experience, ML services production testing experience, Experiment tracking tools knowledge

What You'll Do.

Define ML quality strategy

Define acceptance criteria

Design model evaluation suites

Maintain model evaluation suites

Maintain test datasets

Evaluate CAD RL model outputs

Define structured rubrics

Translate qualitative findings

Automate ML QA workflows

Create test harnesses

Maintain test harnesses

Mentor teams on ML QA

Mentor teams on evaluation standards

Contribute to projects

Contribute to codebases

Ensure code consistency

Participate in code reviews

Provide constructive feedback

How You'll Work.

Team & Collaboration

Work with researchers; Work with ML developers; Work with software developers; Collaborate across research; Collaborate across product; Cross-functional teams; Global team collaboration

Communication Scope

Present findings; Present ideas; Communicate well

Process & Methodology

Agile development

Full Job Description

**Job Requisition ID #** 26WD98377 **Senior Machine Learning Test Engineer** **Location: United States East Coast** **Position Overview** As a Senior Machine Learning Test Engineer in the Research Enablement team, you will work side-by-side with researchers, Machine Learning developers and developers, and software developers and developers to define and uphold quality standards for ML systems. You are a quality-focused developer who is passionate about reliable, repeatable evaluation of ML models and data. Your skills span test strategy, automation, and a little MLOps, with a strong software engineering base. You are excited to collaborate across research and product to ship ML capabilities with clear quality gates. You are comfortable working at the intersection of research and product and are competent in using Autodesk CAD software. Reporting Structure: You will report to an Engineering Manager in Research Enablement. Location: United States, East Coast Time Zone. We are a global team, located in London, San Francisco, Toronto, and remotely. Autodesk is a hybrid-first company, allowing workers to work remotly, in an office, or a mix of both. **Responsibilities** * Define ML quality strategy and acceptance criteria across data, model, and system levels * Design and maintain model evaluation suites, metrics, and test datasets * Evaluating CAD RL model outputs for geometric validity or policy stability * Defining structured rubrics that translate qualitative findings into measurable evaluation gates * Testing ML Models from product side * API Testing * Automate ML QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins) * Create and maintain test harnesses for ML services and APIs * Mentor teams on ML QA best practices and consistent evaluation standards * Build quality gates for training and deployment pipelines (e.g., regression checks, drift detection) * Contribute to multi-team projects and codebases, ensuring code quality and consistency * Participat

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