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AI Specialist - Applied ML Research

Xanadu · Active · JazzHR / ApplyToJob

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FieldValue
CompanyXanadu
TitleAI Specialist - Applied ML Research
Normalized title-
Department / team-
Location-
Work model-
Employment type-
Salary-
Statusactive
ATS providerJazzHR / ApplyToJob
Posted / first seen / 2026-05-30
Changed / last seen2026-05-30 / 2026-06-06

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Linked records

CompanyXanadu
Source407a85b6-c41c-479c-8d15-b2891f50df89
ATS providerJazzHR / ApplyToJob

Description

About Xanadu: Xanadu’s mission is to build quantum computers that are useful and available to people everywhere. At Xanadu, we are learners, innovators, researchers, collaborators and problem solvers. We are creating something that has never been built before. Few people in their life will be able to be a part of something like this, where if we are successful, the technologies we develop will solve some of the world’s most challenging problems, and literally change the world. And that is something to be excited about! Your role and responsibilities: As an AI Specialist at Xanadu, you will drive applied AI initiatives by optimizing the core of our R&D efforts and deeply analyzing diverse R&D data and processes. Your work will focus on enhancing the performance of our most crucial systems, from the design and characterization of our quantum hardware to the execution of internal simulation software on high-performance computing platforms. Using state-of-the-art machine learning, AI techniques, GPU programming, and advanced optimization, you will accelerate our progress toward the first commercially viable quantum computer. The AI team focuses on building and improving modeling, optimization, simulation, data processing, and design methodology for all internal research. At the intersection of multiple technical disciplines, you will collaborate with leading researchers, scientists, engineers, and software developers, using cutting-edge ML to enhance software tools and potentially transform research processes. You will: Develop generalizable representation/reinforcement/generative learning strategies for diverse research data, addressing both theoretical and engineering challenges. Develop and implement ML-based design optimization strategies for hardware and software systems. Investigate and analyze complex structured and unstructured data from various internal R&D projects and products to identify key trends and insights. Continuously monitor, evaluate, and incorporate state-of-the-art ML and AI developments into internal R&D tool stacks to maintain a competitive advantage in quantum hardware progress. Collaborate closely with engineers and scientists to create and implement novel ML-driven solutions for complex research challenges. Establish and maintain reproducible data analysis and modeling workflows. At Xanadu, we primarily work with Python, Jax, GitHub, Docker, CI pipelines, Jupyter and multiple cloud platforms. Proficiency in these technologies is essential. Basic qualifications and experience: BSc. in Physics, Math, Computer Science, Engineering, or a related field. 5+ years of industry experience in ML/AI/deep learning, data science, statistics, physical sciences, physical design and optimization, simulation software, or control systems. Strong knowledge of Python and its numerical/scientific ecosystem (jax, numpy, pandas, xarray, pytorch, cuda, scipy, sklearn, ray, etc.). Deep mathematical understanding of machine learning and optimization. Hands-on experience in one or more of the following focus areas: ML-based optimization and the optimization of numerics or simulation software. Deep learning/AI/ML specializations such as representation learning, reinforcement learning, geometric deep learning, computer vision, NLP, generative models, GFlowNet, or control theory. Designing and building novel and generalizable representations of complex data structures with symmetries. Large-scale training of neural networks for RL, LLMs, diffusion models, or other types of generative modeling. Writing and designing simulators for complex physical systems (e.g., differential equations) and control systems. Experience with GPU programming (e.g., CUDA). Experience with software development lifecycles, including version control, code review, testing, CI/CD, logging, profiling, debugging, and documentation. Comfortable working with Linux shell, Docker, Git, and GitHub. Enthusiasm for learning new technologies and scientific concepts with minimal supervision. Solid communication and collaboration skills. Strong self-driven analytical and problem-solving abilities. Good knowledge of physics, linear algebra, and statistics. Preferred qualifications and experience: MSc/PhD in Computer Science, Engineering, Physics, Math, or related field. Excellent knowledge in physics and linear algebra. Deep experience with representation learning, reinforcement learning, and generative modeling. Familiarity with or curiosity towards quantum computing. Rich experience in any of these areas: Statistical inference GPU programming ML or signal analysis on ultrafast embedded systems Reinforcement learning Training of commercial grade LLMs GFlowNet Geometric deep learning and equivariant models Modeling and simulation of physical systems on HPC Deep learning based computer vision systems This is for an existing position. Your base salary will be determined based on your location, experience, and internal benchmarks. The base salary range is 140,000 - 190,000 CAD. You will also be eligible for equity and benefits.

Full job record

Job ID729b6d24a52dbefb87b917d01f607181aeaa7a67
Org ID39e1b183-16f3-44d6-ada8-713436fe9313
Source ID407a85b6-c41c-479c-8d15-b2891f50df89
Board ID407a85b6-c41c-479c-8d15-b2891f50df89
Providerjazzhr
Provider Job KeyUQp8PbZET4
TitleAI Specialist - Applied ML Research
Normalized Title
Statusactive
Activeyes
Location Text
Department
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Employment Type
Workplace Type
Remote Policy
Country
Region
City
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://xanadu.applytojob.com/apply/UQp8PbZET4/AI-Specialist-Applied-ML-Research
Apply URLhttps://xanadu.applytojob.com/apply/UQp8PbZET4/AI-Specialist-Applied-ML-Research
First Seen At2026-05-30 05:46:38Z
Last Seen At2026-06-06 20:01:08Z
Last Checked At2026-06-06 20:01:08Z
Last Changed At2026-05-30 05:46:38Z
Inactive At
Source Posted At
Source Updated At
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    "url": "https://xanadu.applytojob.com/apply/jobs/details/UQp8PbZET4?&",
    "heading": "AI Specialist - Applied ML Research",
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    "description_html": "<div class=\"job_description\">\n\t\t\t\t\t<p style=\"line-height:1.38;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">About Xanadu:</span></span></span></span></span><br><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Xanadu&#8217;s mission is to build quantum computers that are useful and available to people everywhere.</span></span></span></span></span></span></span></p><p style=\"line-height:1.38;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">At Xanadu, we are learners, innovators, researchers, collaborators and problem solvers. We are creating something that has never been built before. Few people in their life will be able to be a part of something like this, where if we are successful, the technologies we develop will solve some of the world&#8217;s most challenging problems, and literally change the world. And that is something to be excited about!</span></span></span></span></span></span></span></p><p style=\"line-height:1.38;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Your role and responsibilities:</span></span></span></span></span></span></span></p><p style=\"line-height:1.38;margin-bottom:8px;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">As an AI Specialist at Xanadu, you will drive applied AI initiatives by optimizing the core of our R&amp;D efforts and deeply analyzing diverse R&amp;D data and processes. Your work will focus on enhancing the performance of our most crucial systems, from the design and characterization of our quantum hardware to the execution of internal simulation software on high-performance computing platforms. Using state-of-the-art machine learning, AI techniques, GPU programming, and advanced optimization, you will accelerate our progress toward the first commercially viable quantum computer. The AI team focuses on building and improving modeling, optimization, simulation, data processing, and design methodology for all internal research. At the intersection of multiple technical disciplines, you will collaborate with leading researchers, scientists, engineers, and software developers, using cutting-edge ML to enhance software tools and potentially transform research processes.</span></span></span></span></span></span></span></p><p style=\"line-height:1.38;margin-bottom:8px;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">You will:</span></span></span></span></span></span></span></p><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Develop generalizable representation/reinforcement/generative learning strategies for diverse research data, addressing both theoretical and engineering challenges.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Develop and implement ML-based design optimization strategies for hardware and software systems.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Investigate and analyze complex structured and unstructured data from various internal R&amp;D projects and products to identify key trends and insights.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Continuously monitor, evaluate, and incorporate state-of-the-art ML and AI developments into internal R&amp;D tool stacks to maintain a competitive advantage in quantum hardware progress.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Collaborate closely with engineers and scientists to create and implement novel ML-driven solutions for complex research challenges.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Establish and maintain reproducible data analysis and modeling workflows.</span></span></span></span></span></span></span></li></ul><p style=\"line-height:1.38;margin-top:8px;margin-bottom:8px;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">At Xanadu, we primarily work with Python, Jax, GitHub, Docker, CI pipelines, Jupyter and multiple cloud platforms. Proficiency in these technologies is essential.</span></span></span></span></span></span></span></p><p style=\"line-height:1.38;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Basic qualifications and experience:</span></span></span></span></span></span></span></p><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">BSc. in Physics, Math, Computer Science, Engineering, or a related field.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">5+ years of industry experience in ML/AI/deep learning, data science, statistics, physical sciences, physical design and optimization, simulation software, or control systems.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Strong knowledge of Python and its numerical/scientific ecosystem (jax, numpy, pandas, xarray, pytorch, cuda, scipy, sklearn, ray, etc.).</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Deep mathematical understanding of machine learning and optimization.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Hands-on experience in one or more of the following focus areas:</span></span></span></span></span></span></span><ul><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">ML-based optimization and the optimization of numerics or simulation software.</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Deep learning/AI/ML specializations such as representation learning, reinforcement learning, geometric deep learning, computer vision, NLP, generative models, GFlowNet, or control theory.</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Designing and building novel and generalizable representations of complex data structures with symmetries.</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Large-scale training of neural networks for RL, LLMs, diffusion models, or other types of generative modeling.</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Writing and designing simulators for complex physical systems (e.g., differential equations) and control systems.</span></span></span></span></span></span></span></li></ul></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience with GPU programming (e.g., CUDA).</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience with software development lifecycles, including version control, code review, testing, CI/CD, logging, profiling, debugging, and documentation.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Comfortable working with Linux shell, Docker, Git, and GitHub.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Enthusiasm for learning new technologies and scientific concepts with minimal supervision.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Solid communication and collaboration skills.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Strong self-driven analytical and problem-solving abilities.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Good knowledge of physics, linear algebra, and statistics.</span></span></span></span></span></span></span></li></ul><p style=\"line-height:1.38;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Preferred qualifications and experience:</span></span></span></span></span></span></span></p><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">MSc/PhD in Computer Science, Engineering, Physics, Math, or related field.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Excellent knowledge in physics and linear algebra.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Deep experience with representation learning, reinforcement learning, and generative modeling.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Familiarity with or curiosity towards quantum computing.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Rich experience in any of these areas:</span></span></span></span></span></span></span><ul><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Statistical inference</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">GPU programming</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">ML or signal analysis on ultrafast embedded systems</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Reinforcement learning</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Training of commercial grade LLMs</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">GFlowNet</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Geometric deep learning and equivariant models</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Modeling and simulation of physical systems on HPC</span></span></span></span></span></span></span></li><li style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"color:#3b3d4d;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Deep learning based computer vision systems</span></span></span></span></span></span></span></li></ul></li></ul><div style=\"list-style-type:circle;\"><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\">This is for an existing position. Your base salary will be determined based on your location, experience, and internal benchmarks. The base salary range is 140,000 - 190,000 CAD. You will also be eligible for equity and benefits.</span></span>",
    "description_text": "About Xanadu:\n Xanadu’s mission is to build quantum computers that are useful and available to people everywhere.\n At Xanadu, we are learners, innovators, researchers, collaborators and problem solvers. We are creating something that has never been built before. Few people in their life will be able to be a part of something like this, where if we are successful, the technologies we develop will solve some of the world’s most challenging problems, and literally change the world. And that is something to be excited about!\n Your role and responsibilities:\n As an AI Specialist at Xanadu, you will drive applied AI initiatives by optimizing the core of our R&D efforts and deeply analyzing diverse R&D data and processes. Your work will focus on enhancing the performance of our most crucial systems, from the design and characterization of our quantum hardware to the execution of internal simulation software on high-performance computing platforms. Using state-of-the-art machine learning, AI techniques, GPU programming, and advanced optimization, you will accelerate our progress toward the first commercially viable quantum computer. The AI team focuses on building and improving modeling, optimization, simulation, data processing, and design methodology for all internal research. At the intersection of multiple technical disciplines, you will collaborate with leading researchers, scientists, engineers, and software developers, using cutting-edge ML to enhance software tools and potentially transform research processes.\n You will:\n Develop generalizable representation/reinforcement/generative learning strategies for diverse research data, addressing both theoretical and engineering challenges.\n Develop and implement ML-based design optimization strategies for hardware and software systems.\n Investigate and analyze complex structured and unstructured data from various internal R&D projects and products to identify key trends and insights.\n Continuously monitor, evaluate, and incorporate state-of-the-art ML and AI developments into internal R&D tool stacks to maintain a competitive advantage in quantum hardware progress.\n Collaborate closely with engineers and scientists to create and implement novel ML-driven solutions for complex research challenges.\n Establish and maintain reproducible data analysis and modeling workflows.\n At Xanadu, we primarily work with Python, Jax, GitHub, Docker, CI pipelines, Jupyter and multiple cloud platforms. Proficiency in these technologies is essential.\n Basic qualifications and experience:\n BSc. in Physics, Math, Computer Science, Engineering, or a related field.\n 5+ years of industry experience in ML/AI/deep learning, data science, statistics, physical sciences, physical design and optimization, simulation software, or control systems.\n Strong knowledge of Python and its numerical/scientific ecosystem (jax, numpy, pandas, xarray, pytorch, cuda, scipy, sklearn, ray, etc.).\n Deep mathematical understanding of machine learning and optimization.\n Hands-on experience in one or more of the following focus areas: ML-based optimization and the optimization of numerics or simulation software.\n Deep learning/AI/ML specializations such as representation learning, reinforcement learning, geometric deep learning, computer vision, NLP, generative models, GFlowNet, or control theory.\n Designing and building novel and generalizable representations of complex data structures with symmetries.\n Large-scale training of neural networks for RL, LLMs, diffusion models, or other types of generative modeling.\n Writing and designing simulators for complex physical systems (e.g., differential equations) and control systems.\n Experience with GPU programming (e.g., CUDA).\n Experience with software development lifecycles, including version control, code review, testing, CI/CD, logging, profiling, debugging, and documentation.\n Comfortable working with Linux shell, Docker, Git, and GitHub.\n Enthusiasm for learning new technologies and scientific concepts with minimal supervision.\n Solid communication and collaboration skills.\n Strong self-driven analytical and problem-solving abilities.\n Good knowledge of physics, linear algebra, and statistics.\n Preferred qualifications and experience:\n MSc/PhD in Computer Science, Engineering, Physics, Math, or related field.\n Excellent knowledge in physics and linear algebra.\n Deep experience with representation learning, reinforcement learning, and generative modeling.\n Familiarity with or curiosity towards quantum computing.\n Rich experience in any of these areas: Statistical inference\n GPU programming\n ML or signal analysis on ultrafast embedded systems\n Reinforcement learning\n Training of commercial grade LLMs\n GFlowNet\n Geometric deep learning and equivariant models\n Modeling and simulation of physical systems on HPC\n Deep learning based computer vision systems\n This is for an existing position. Your base salary will be determined based on your location, experience, and internal benchmarks. The base salary range is 140,000 - 190,000 CAD. You will also be eligible for equity and benefits.",
    "jsonld_jobposting": null
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  "list_job": {
    "id": "UQp8PbZET4",
    "title": "AI Specialist - Applied ML Research",
    "detailUrl": "https://xanadu.applytojob.com/apply/jobs/details/UQp8PbZET4?&"
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