At a Glance
- Tasks: Build scalable ML training pipelines and collaborate with AI researchers on innovative projects.
- Company: Join Autodesk, a leader in software that shapes the future of design and creativity.
- Benefits: Enjoy remote work flexibility, competitive salary, and a culture that values diversity and belonging.
- Why this job: Make a real impact on how designers interact with AI tools and revolutionise the built environment.
- Qualifications: BSc/MSc in Computer Science or equivalent experience; strong skills in ML infrastructure and Python required.
- Other info: Work with a global team and enjoy regular offsite events for collaboration and connection.
The predicted salary is between 48000 - 84000 £ per year.
Principal Machine Learning Operations Developer for AI Research page is loaded
Principal Machine Learning Operations Developer for AI Research
Apply locations London, GBR time type Full time posted on Posted 12 Days Ago job requisition id 25WD90720
Job Requisition ID #
25WD90720
Job Title: Principal Machine Learning Operations Developer for AI Research
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.
As a MLOps Developers at Autodesk Research, you will be working side-by-side with world-class AI researchers to build and scale foundation models trained on design data. You will focus on overcoming the challenges associated with large-scale model training and processing of vast amounts of diverse design data. Your expertise in distributed systems, ML infrastructure, and data engineering will be crucial in developing the next generation of ML-powered product features that will help our customers imagine, design, and make a better world.
You\’ll be joining a rapidly growing team working on a project that aims to revolutionize the design of nearly every aspect of the built environment. Your contributions will directly influence how designers, architects, and engineers interact with AI tools in the future.
This role is fully remote-friendly. Our team operates primarily remotely with team members distributed across the globe, with offices in London, Boston, Toronto and other locations worldwide. At Autodesk, we embrace remote work while fostering connection through regular team offsites for collaborative planning and relationship building. This balanced approach ensures you can work where you\’re most productive while maintaining meaningful connections with colleagues.
Responsibilities
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Support AI researchers by building scalable ML training pipelines and infrastructure for foundation model development
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Design efficient data processing workflows for large-scale design datasets and industry-specific file formats
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Optimize distributed training systems and develop solutions for model parallelism, checkpointing, and efficient resource management
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Analyze performance bottlenecks and provide solutions to scaling problems
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Implement and maintain robust, testable code that is well documented and easy to understand
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Collaborate on projects at the intersection of research and product with a diverse, global team of researchers and engineers
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Present results to collaborators and leadership
Minimum Qualifications
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BSc or MSc in Computer Science or related field, or equivalent industry experience
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Experience with distributed systems for machine learning and deep learning at scale
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Strong knowledge of ML infrastructure and model parallelism techniques, including frameworks like PyTorch , Lightning, Megatron, DeepSpeed, and FSDPProficiency in Python and strong software engineering practices
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Experience with cloud services and architectures (AWS, Azure, etc.)
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Familiarity with version control, CI/CD, and deployment pipelines
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Excellent written documentation skills to document code, architectures, and experiments
Preferred Qualifications
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Experience with AEC data formats (e.g., BIM models, IFC files, CAD files, Drawing Sets)
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Knowledge of the AEC industry and its specific data processing challenges
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Experience scaling ML training and data pipelines for large datasets
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Experience with distributed data processing and ML infrastructure (e.g., Apache Spark, Ray, Docker, Kubernetes)
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Experience with performance optimization, monitoring, and efficiency in large-scale ML systems
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Experience with Autodesk or similar products (Revit, Sketchup, Forma)
The Ideal Candidate
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A self-starter who can solve problems with minimal supervision while collaborating effectively with a global, remote-first team
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Adaptable and creative, comfortable building new infrastructure or working within existing codebases
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Thrives in ambiguous, rapidly evolving areas where learning and flexibility are essential
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Excellent communicator who can convey complex technical concepts clearly to diverse audiences
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Learn More
About Autodesk
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!
Salary transparency
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. Learn more here:
Are you an existing contractor or consultant with Autodesk?
Please search for open jobs and apply internally (not on this external site).
Shape the world, shape your future
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!
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Principal Machine Learning Operations Developer for AI Research employer: Autodesk, Inc.
Contact Detail:
Autodesk, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Machine Learning Operations Developer for AI Research
✨Tip Number 1
Familiarise yourself with the specific tools and frameworks mentioned in the job description, such as PyTorch, Apache Spark, and Docker. Having hands-on experience or projects showcasing your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Engage with the AI and MLOps community online. Participate in forums, attend webinars, or join relevant groups on platforms like LinkedIn. This not only helps you stay updated on industry trends but also allows you to network with professionals who might provide insights or referrals.
✨Tip Number 3
Prepare to discuss your problem-solving approach during interviews. Be ready to share specific examples of how you've tackled challenges in distributed systems or ML infrastructure, as this role requires a strong ability to analyse and optimise performance bottlenecks.
✨Tip Number 4
Showcase your adaptability and creativity by discussing any projects where you've had to build new infrastructure or work within existing codebases. Highlighting your ability to thrive in ambiguous situations will resonate well with the team at Autodesk.
We think you need these skills to ace Principal Machine Learning Operations Developer for AI Research
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning operations, distributed systems, and data engineering. Use keywords from the job description to demonstrate that you meet the qualifications.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI research and how your skills align with Autodesk's mission. Mention specific projects or experiences that showcase your ability to build scalable ML training pipelines.
Showcase Technical Skills: Clearly outline your proficiency in Python, cloud services, and ML frameworks like PyTorch. Provide examples of how you've implemented these technologies in past projects to solve complex problems.
Highlight Collaboration Experience: Since the role involves working with a global team, emphasise your experience in collaborative projects. Share examples of how you've effectively communicated technical concepts to diverse audiences.
How to prepare for a job interview at Autodesk, Inc.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with distributed systems and ML infrastructure. Highlight specific projects where you've implemented solutions using frameworks like PyTorch, Docker, or Kubernetes.
✨Understand the AEC Industry
Familiarise yourself with AEC data formats and the unique challenges they present. This knowledge will demonstrate your commitment to the role and your ability to contribute effectively from day one.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. As you'll be collaborating with a diverse team, being able to convey your ideas clearly is crucial for success.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially in scaling ML training and optimising performance. Think of examples from your past experiences where you overcame significant challenges.