At a Glance
- Tasks: Define quality standards for ML systems and automate QA workflows using Python.
- Company: Join Autodesk, a global leader in innovative design software.
- Benefits: Competitive salary, bonuses, stock options, and comprehensive benefits package.
- Other info: Hybrid work environment with opportunities for global collaboration and career growth.
- Why this job: Make an impact on cutting-edge ML projects while collaborating with top talent.
- Qualifications: 7+ years in software engineering or QA for ML/AI systems, strong Python skills.
The predicted salary is between 60000 - 80000 £ per year.
As a Senior Machine Learning QA Engineer in the Research Enablement team, you will work side-by-side with researchers, Machine Learning Engineers and software engineers to define and uphold quality standards for ML systems. You are a quality-focused engineer 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 Kingdom. We are a global team, located in London, San Francisco, Toronto, and remotely. Autodesk is a hybrid-first company, allowing workers to work remotely, 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
- Evaluate CAD RL model outputs for geometric validity or policy stability
- Define structured rubrics that translate qualitative findings into measurable evaluation gates
- Test 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
- Participate in code reviews and provide constructive feedback to peers
- Document and present findings and ideas across the company
Minimum Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience
- 7+ years of professional experience in software engineering or QA for ML/AI systems
- Strong programming skills in Python, with experience in test automation
- Familiarity with popular CAD environments tooling
- Proficient in Automation and UAT test suite/framework
- Experience designing QA frameworks or platforms used by multiple teams
- Excellent problem-solving skills and attention to detail
- Strong communication and collaboration skills
- Understanding of software architecture and design patterns
- Ability to work in an agile development environment
Preferred Qualifications:
- Experience with data validation tooling (e.g., Great Expectations) or labeling workflows
- Familiarity with ML frameworks (e.g., PyTorch, TensorFlow)
- Experience with CI/CD tools and processes
- Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow)
- Familiarity with MLOps practices (model monitoring, drift, deployment checks)
- Experience with ML evaluation methods, metrics, and benchmarking
- Passion for learning new technologies and improving existing systems
- Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform)
- Experience testing ML services in production environments
- Knowledge of experiment tracking tools (e.g., Comet, MLflow, Weights & Biases)
The Ideal Candidate:
- Demonstrates initiative to provide solutions and to learn and develop new technologies
- Comfortable building QA systems from scratch and writing maintainable automation
- Enjoys learning and collaborating across global locations
- Comfortable working in newly forming ambiguous areas
- Comfortable building scalable and maintainable systems that will be relied on by others
- Communicates well with others
Benefits: Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
Diversity & Belonging: We take pride in cultivating a culture of belonging where everyone can thrive.
Senior Machine Learning Test Engineer United Kingdom in Cambridge employer: Autodesk
Autodesk is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Senior Machine Learning Test Engineer role. With a hybrid-first approach, employees enjoy the flexibility of remote or in-office work while being part of a global team dedicated to quality in machine learning systems. The company prioritises employee growth through mentorship opportunities and a commitment to diversity and belonging, making it an ideal place for those seeking meaningful and rewarding careers in technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Test Engineer United Kingdom in Cambridge
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Autodesk or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Autodesk.
✨Tap into Online Developer Communities
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We think you need these skills to ace Senior Machine Learning Test Engineer United Kingdom in Cambridge
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Autodesk.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Autodesk and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Autodesk
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Autodesk uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
