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Principal Engineer- Machine Learning

Job Requisition ID #24WD84408Position OverviewAutodesk is a global leader in software for designers, engineers, builders, and creators. Our Design and Make Platform empowers our customers with the technology to create the world around us.We are seeking an experienced Principal Machine Learning Engineer in our Digital Experience Machine Learning team. You will be bringing a wealth of experience in personalizing customers’ digital experience on our ecommerce platform. At Autodesk, Machine Learning Engineers are both data/research scientists and software engineers, who develop and implement machine learning models and algorithms. Unlike other companies that separate these roles, our engineers work on projects from ideation to implementation.We are a global team. This is a hybrid role and you will report to Director of Machine Learning Engineering in Digital Experience team.Responsibilities• As a Principal Machine Learning Engineer at Autodesk, you will be responsible for the development and training of cutting-edge machine learning models and algorithms that can effectively leverage our platform activities and industry trends to create personalized recommendations that are delivered to our customers at the optimal moment• Work with BIG data, build scalable AI innovations• Write production quality code and influence the next generation of Autodesk customer experience• Test and Deploy Production Models: Automate ML model testing• Implement and use CI/CD pipelines to ensure seamless model deployment• Monitor Model Health and Performance: Define, implement, and continuously monitor health metrics for deployed models• Manage Re-Training Pipelines: Take ownership of the re-training pipeline for deployed ML models, ensuring they are continuously updated and optimized for performance• Optimize Performance and Efficiency: Identify opportunities to enhance model performance, reduce computational costs, and minimize latency. Implement best practices to achieve these goals• Product Ownership: Adopt a full product ownership mindset, escalating issues when necessary and effectively presenting results and insights to stakeholders and leadershipMinimum Qualifications• Bachelor's or master's degree in computer science, a related technical field, or equivalent practical experience• 6+ years of hands-on experience in machine learning design, development and deployment• 6+ years of hands-on experience with data mining, and information retrieval or natural language processing• Hands-on experience in online machine learning model deployment in a cloud service such as AWS• Strong background in API development (REST) with experience in designing and implementing robust solutions• Expert-level proficiency in programming languages such as Java, Python, etc.• Proven track record of leading fast-paced engineering teams to tackle large-scale AI problems• Track record of producing papers in conferences such as KDD, WWW, WSDM, and Patenting Innovations• Experienced in Agile development environments, with a proven ability to adapt to dynamic team structures• Skilled at collaborating with distributed teams across various geographies and time zones• Proven leadership in incident response, including driving root cause analysis and implementing preventive measuresLearn MoreAbout AutodeskWelcome 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 – our Culture Code is at the core of everything we do. Our values and ways of working help our people thrive and realize their potential, which leads to even better outcomes for our customers.When you’re an Autodesker, you can be your whole, authentic self and do meaningful work that helps build a better future for all. Ready to shape the world and your future? Join us!BenefitsFrom health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/Salary transparencySalary is one part of Autodesk’s competitive compensation package. For U.S.-based roles, we expect a starting base salary between $146,900 and $237,600. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, we also have a significant emphasis on annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.Equal Employment OpportunityAt Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.Diversity & BelongingWe take pride in cultivating a culture of belonging and an equitable workplace where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belongingAre you an existing contractor or consultant with Autodesk?Please search for open jobs and apply internally (not on this external site).
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What You Should Know About Principal Engineer- Machine Learning, Autodesk

Do you want to take your machine learning expertise to the next level and make a significant impact at a leading software company? Join Autodesk as a Principal Machine Learning Engineer in beautiful San Francisco, CA! In this hybrid role, you’ll be part of the Digital Experience Machine Learning team, where you’ll get the chance to create personalized digital experiences for our customers on our ecommerce platform. You'll be responsible for developing and training innovative machine learning models and algorithms, building scalable AI solutions, and writing production-quality code. Not only will you have the opportunity to leverage big data, but you'll also ensure that our models are deployed seamlessly using CI/CD pipelines, monitoring their health and performance. With over 6 years of hands-on experience in machine learning design and deployment, and proficiency in programming languages like Java and Python, you'll lead fast-paced engineering teams, collaborating with diverse global teams. At Autodesk, we pride ourselves on our culture and values that foster innovation and inclusivity. If you’re ready to shape the future while showcasing your skills and creativity, Autodesk welcomes you. Let’s create amazing things together!

Frequently Asked Questions (FAQs) for Principal Engineer- Machine Learning Role at Autodesk
What are the responsibilities of a Principal Machine Learning Engineer at Autodesk?

As a Principal Machine Learning Engineer at Autodesk, you will develop and train cutting-edge machine learning models to personalize customer experiences, leverage big data for AI innovations, and automate model testing and deployment. Your role also includes monitoring model health and performance, managing re-training pipelines, and optimizing performance and efficiency to minimize costs and latency.

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What qualifications are required to become a Principal Machine Learning Engineer at Autodesk?

To qualify for the Principal Machine Learning Engineer position at Autodesk, you need a Bachelor's or Master's degree in computer science or a related field, along with at least 6 years of experience in machine learning design, development, and deployment. A strong background in natural language processing, online model deployment in a cloud service such as AWS, and expertise in programming languages like Java and Python are essential.

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How can I apply for the Principal Machine Learning Engineer position at Autodesk?

You can apply for the Principal Machine Learning Engineer role at Autodesk through our career website. Be sure to showcase your relevant experience, particularly in machine learning and software engineering, in your resume and cover letter to increase your chances of being selected for an interview.

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What is the work culture like for a Principal Machine Learning Engineer at Autodesk?

The work culture at Autodesk for a Principal Machine Learning Engineer is inclusive and collaborative, emphasizing innovation and diversity. Engineers work in hybrid settings, allowing for flexibility, and Autodesk encourages team members to express their authentic selves, promoting an environment where everyone can thrive and make meaningful contributions.

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What opportunities for advancement exist for Principal Machine Learning Engineers at Autodesk?

At Autodesk, Principal Machine Learning Engineers have ample opportunities for advancement, including leadership roles within the engineering team or cross-functional projects. The company invests in employee growth through professional development programs and encourages participation in conferences and tech innovation.

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Common Interview Questions for Principal Engineer- Machine Learning
Can you describe a machine learning project you have led from ideation to implementation?

When answering this question, focus on a specific project that showcases your skills in machine learning. Describe the problem you aimed to solve, your approach to designing and implementing the solution, and the results achieved. Highlight team collaboration and any challenges faced during the process.

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How do you ensure the quality of machine learning models in production?

To ensure the quality of machine learning models in production, emphasize the importance of automated testing, continuous integration, and continuous deployment (CI/CD) pipelines. Discuss how you define and monitor health metrics and performance indicators, and elaborate on your experiences with model versioning and retraining procedures.

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What programming languages are you most proficient in, and how have you used them in your machine learning work?

Discuss your proficiency in programming languages, particularly Java and Python, and provide examples of how you've utilized these languages for machine learning tasks. You might mention libraries like TensorFlow or scikit-learn that you've worked with, and how these tools helped you deliver successful projects.

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How do you approach collaboration with distributed teams?

When discussing your approach to collaborating with distributed teams, emphasize communication strategies you've used, such as regular meetings and using collaboration tools. Highlight any specific experience where coordinating with team members across various time zones led to a successful project outcome.

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What methodologies do you use in your machine learning projects?

Mention any Agile methodologies you've applied in your previous projects. Discuss how these methodologies helped in adapting to dynamic environments, improving team productivity, and how they facilitated better communication and project management throughout the development cycle.

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Can you explain a technical concept related to machine learning to a non-technical audience?

In response, choose a straightforward concept, like overfitting or clustering, and relate it to a simple analogy or real-world example. This will showcase your ability to communicate complex ideas clearly and effectively to non-technical stakeholders.

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What steps would you take to optimize a deployed machine learning model?

Describe the steps you would take to optimize a deployed machine learning model, focusing on performance metrics such as accuracy, speed, and resource usage. Discuss the importance of monitoring model health and implementing feedback loops for continuous improvement.

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Have you ever encountered a failure in your machine learning deployment? How did you handle it?

Share a specific experience where a machine learning deployment did not go as planned, discussing the reasons for the failure and the steps you took to troubleshoot and rectify the situation. Emphasize your learning experience and how it informed your future projects.

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In your opinion, what is the future of machine learning in the software industry?

Discuss your perspective on the future development of machine learning, integrating aspects like automation, the rise of AI applications, and ethical considerations. Highlight how these trends may shape roles like the Principal Machine Learning Engineer at companies like Autodesk.

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What are some successful techniques you have used to present findings to stakeholders?

Discuss your techniques for effectively communicating machine learning findings, such as using clear visuals, focusing on actionable insights, and tailoring your presentation to your audience's level of familiarity with technical concepts. Highlight any successful presentations to stakeholders that led to significant decisions.

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Autodesk’s mission is to empower innovators with design and make technology so they can achieve the new possible. Our technology spans architecture, engineering and construction, product design and manufacturing, and media and entertainment, empo...

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Full-time, hybrid
DATE POSTED
December 21, 2024

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