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AI Research Scientist

AT Autodesk
Autodesk

AI Research Scientist

San Francisco, CA

Job Requisition ID #

24WD75583

Position Overview

As an AI Research Scientist at Autodesk Research, you will be doing fundamental and applied research that will help our customers imagine, design, and make a better world. We are a team of scientists, researchers, engineers, and designers working together on projects that range from learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design and construction.

As a member of the AI Lab in Autodesk Research you will be an expert in research areas such as artificial intelligence, deep learning, generative AI, machine learning, computer vision, reinforcement learning, information retrieval, and natural language processing.

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Autodesk's AI Lab is active in the wider research community, targeting publications at CVPR, NeurIPS, ICML, ICLR, SIGGRAPH, and other top-tier conferences. We collaborate with top academic & industry labs, combining the best of an academic environment with product-guided research. We are a global team, located in London, San Francisco, Toronto, and remotely.

The role will report to a Manager of Research Science in the AI Lab

Location: London, United Kingdom, Germany, or Italy

Responsibilities

  • Develop new ML models and AI techniques
  • Lead on research projects within a global team
  • Review relevant AI/ML literature to identify emerging methods, technologies, and best practices
  • Work towards long-term research goals, while identifying intermediate milestones
  • Build relationships and collaborate with academics and institutions
  • Explore new data sources and discover techniques for best leveraging data
  • Publish papers; attend and speak at conferences
  • You will be strategically about research directions

Minimum Qualifications

  • A Master's or PhD in a field related to AI/ML such as: Computer Science, Mathematics, Statistics, Physics, Linguistics, Mechanical Engineering, Architecture or related disciplines
  • Publication track record in machine learning conferences and/or journals
  • Significant post-graduate research experience, or 5 or greater years of work experience (actual job title/position will be commensurate to experience)
  • Good background in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.)
  • Familiarity with Deep Learning techniques (e.g. Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.)
  • Familiarity with PyTorch, TensorFlow, JAX or similar frameworks
  • Strong coding abilities in Python and/or C++

Preferred Qualifications

  • 2D & 3D Generative AI
  • Reinforcement Learning
  • LLMs and Natural Language Processing
  • Computational geometry and geometric methods (e.g. shape analysis, topology, differential geometry, discrete geometry, functional mapping, geometric deep learning, graph neural networks)
  • Multi-modal deep learning and/or information retrieval
  • Architecture, Construction, Manufacturing, Media & Entertainment or other Autodesk domains

#LI-JK3

At 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.

Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). If you have any questions or require support, contact Autodesk Careers.

Client-provided location(s): San Francisco, CA, USA; Toronto, ON, Canada
Job ID: autodesk-24WD75583
Employment Type: Other

Perks and Benefits

  • Health and Wellness

    • Long-Term Disability
    • FSA With Employer Contribution
    • HSA
    • HSA With Employer Contribution
    • Fitness Subsidies
    • FSA
    • Health Insurance
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • Short-Term Disability
    • Health Reimbursement Account
    • On-Site Gym
    • Pet Insurance
    • Mental Health Benefits
  • Parental Benefits

    • Fertility Benefits
    • Adoption Assistance Program
    • Family Support Resources
    • Non-Birth Parent or Paternity Leave
    • Birth Parent or Maternity Leave
    • Adoption Leave
  • Work Flexibility

    • Flexible Work Hours
    • Remote Work Opportunities
    • Hybrid Work Opportunities
    • Work-From-Home Stipend
  • Office Life and Perks

    • Some Meals Provided
    • Commuter Benefits Program
    • Casual Dress
    • Pet-friendly Office
    • Happy Hours
    • Snacks
    • Company Outings
  • Vacation and Time Off

    • Personal/Sick Days
    • Paid Holidays
    • Unlimited Paid Time Off
    • Leave of Absence
    • Paid Vacation
    • Sabbatical
    • Volunteer Time Off
  • Financial and Retirement

    • Relocation Assistance
    • Performance Bonus
    • Stock Purchase Program
    • Company Equity
    • 401(K) With Company Matching
  • Professional Development

    • Shadowing Opportunities
    • Access to Online Courses
    • Promote From Within
    • Learning and Development Stipend
    • Lunch and Learns
    • Tuition Reimbursement
    • Mentor Program
    • Internship Program
    • Leadership Training Program
    • Professional Coaching
    • Associate or Rotational Training Program
  • Diversity and Inclusion

    • Diversity, Equity, and Inclusion Program
    • Employee Resource Groups (ERG)
    • Woman founded/led
    • Black founded/led
    • BIPOC founded/led
    • Latinx founded/led
    • Asian founded/led
    • LGBTQ+ founded/led
    • Veteran founded/led