Photonics Engineer - Experimental Statistician

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    "heading": "Photonics Engineer - Experimental Statistician",
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    "description_html": "<div class=\"job_description\">\n\t\t\t\t\t<p style=\"line-height:1.656;margin-top:16px;margin-bottom:16px;\"><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></span></span></p><p style=\"line-height:1.656;margin-top:16px;margin-bottom:16px;\"><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;\">Xanadu&#8217;s mission is to build useful quantum computers. We are a team of learners, innovators, and problem solvers, creating technology that has never been built before. Few people get to be a part of something like this&#8212;a journey where success can lead to solving some of the world's most challenging problems and fundamentally changing the world</span></span></span></span></span></span></span></p><p style=\"line-height:1.656;margin-top:16px;margin-bottom:16px;\"><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:1.656;margin-top:16px;margin-bottom:16px;\"><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 a Photonics Engineer - Experimental Statistician in the photonics integration group, you will join the Test and Measurement team to drive the iteration of on-chip photonic devices&#8212;the foundational building blocks of Xanadu's Fault-Tolerant Quantum Computer. This is a software-centric role requiring expertise in statistical modeling to extract device performance and fabrication variability with quantified uncertainties. This analysis will inform future experimental design and guide iteration toward ambitious device performance targets. You will be instrumental in automating and streamlining these analyses at scale to lower design-iteration times and extract insights from large experimental datasets.</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;\">Apply statistical expertise to design experiments for extracting key performance metrics.&#160;</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 with physicists and engineers to apply statistical techniques and guide critical design decisions.&#160;&#160;</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, validate, and deploy scalable statistical models to characterize performance and fabrication variability in photonic devices.</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;\">Build hierarchical models to separate different sources of variability in device performance.</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;\">Contribute to robust, documented Python software libraries for automated, large-scale data analysis pipelines.</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;\">Quantify uncertainties, build noise models for measurements.</span></span></span></span></span></span></span></li></ul><p style=\"line-height:1.656;margin-top:16px;margin-bottom:16px;\"><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;\">Education: MSc or PhD in Statistics, Physics, Astronomy, Data Science 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;\">Experience: 4+ years of experience working with statistics and experiment-based data.</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;\">Expertise in Statistical Inference:</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;\">Inverse problem/parameter inference.&#160;</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;\">Likelihood estimation.&#160;</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;\">Hierarchical modelling.</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;\">Sampling techniques such as MCMCs.</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;\">Outlier detection and rejection.&#160;</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;\">Estimation of confidence intervals and credible intervals.&#160;</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;\">Strong programming skills.&#160;</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;\">Fluency with software data structures and design principles.</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;\">Experience with Git and the pull request workflow.</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;\">Fluency with python data analysis libraries such as NumPy, SciPy, and pandas.</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;\">Applicants will be expected to demonstrate proficiency writing python code.</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;\">Detail and documentation oriented.&#160;</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 communication skills and the ability to thrive in a fast-paced research environment.</span></span></span></span></span></span></span></li></ul><p style=\"line-height:1.656;margin-top:16px;margin-bottom:16px;\"><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;\">PhD in Statistics, Physics, Astronomy, Data Science 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;\">Direct experience with optical or photonic experiment and theory or analogous physical theory.&#160;</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 building statistical models using scientific data.&#160;</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 developing performant software for analyzing large physical data sets.</span></span></span></span></span></span></span></li></ul><span style=\"font-size:14px;\"><span style=\"font-family:Arial, Helvetica, sans-serif;\">This is for a new position.&#160;Your base salary will be determined based on your location, experience, and internal benchmarks. The base salary range is 100,000 - 140,000 CAD. You will also be eligible for equity and benefits.</span></span><p> </p>\n\n<p><span style=\"font-size:12px\"><span style=\"font-family:Arial,Helvetica,sans-serif\">Our values are important. They are fundamental and lay the foundation for culture at Xanadu. Learn more about our values <a href=\"https://www.xanadu.ai/values\">here</a>.</span></span></p>\n\n<p><span style=\"font-size:12px\"><span style=\"font-family:Arial,Helvetica,sans-serif\">We are an equal opportunity employer and encourage candidates of all backgrounds to apply. We are committed to building an inclusive, safe, and equitable culture and fostering an environment where our employees feel included, valued, and heard. We are committed to meeting the needs of all individuals and support a barrier-free workplace. Should you require accommodations at any point during the recruitment process please contact Recruiting at <a href=\"/cdn-cgi/l/email-protection#c0b2a5a3b2b5a9b4a9aea7e6e3f6f4fbb8a1aea1a4b5eea1a9\">recruiting&#64;xanadu.ai</a>. </span></span></p>\n\n<p><span style=\"font-size:12px\"><span style=\"font-family:Arial,Helvetica,sans-serif\">Please be advised that we may use artificial intelligence (AI) tools to assist in the screening and assessment of applicants for this position. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</span></span></p>",
    "description_text": "About Xanadu:\n Xanadu’s mission is to build useful quantum computers. We are a team of learners, innovators, and problem solvers, creating technology that has never been built before. Few people get to be a part of something like this—a journey where success can lead to solving some of the world's most challenging problems and fundamentally changing the world\n Your role and responsibilities:\n As a Photonics Engineer - Experimental Statistician in the photonics integration group, you will join the Test and Measurement team to drive the iteration of on-chip photonic devices—the foundational building blocks of Xanadu's Fault-Tolerant Quantum Computer. This is a software-centric role requiring expertise in statistical modeling to extract device performance and fabrication variability with quantified uncertainties. This analysis will inform future experimental design and guide iteration toward ambitious device performance targets. You will be instrumental in automating and streamlining these analyses at scale to lower design-iteration times and extract insights from large experimental datasets.\n Apply statistical expertise to design experiments for extracting key performance metrics.\n Collaborate with physicists and engineers to apply statistical techniques and guide critical design decisions.\n Develop, validate, and deploy scalable statistical models to characterize performance and fabrication variability in photonic devices.\n Build hierarchical models to separate different sources of variability in device performance.\n Contribute to robust, documented Python software libraries for automated, large-scale data analysis pipelines.\n Quantify uncertainties, build noise models for measurements.\n Basic qualifications and experience:\n Education: MSc or PhD in Statistics, Physics, Astronomy, Data Science or related field.\n Experience: 4+ years of experience working with statistics and experiment-based data.\n Expertise in Statistical Inference: Inverse problem/parameter inference.\n Likelihood estimation.\n Hierarchical modelling.\n Sampling techniques such as MCMCs.\n Outlier detection and rejection.\n Estimation of confidence intervals and credible intervals.\n Strong programming skills.  Fluency with software data structures and design principles.\n Experience with Git and the pull request workflow.\n Fluency with python data analysis libraries such as NumPy, SciPy, and pandas.\n Applicants will be expected to demonstrate proficiency writing python code.\n Detail and documentation oriented.\n Excellent communication skills and the ability to thrive in a fast-paced research environment.\n Preferred qualifications and experience:\n PhD in Statistics, Physics, Astronomy, Data Science or related field.\n Direct experience with optical or photonic experiment and theory or analogous physical theory.\n Experience building statistical models using scientific data.\n Experience developing performant software for analyzing large physical data sets.\n This is for a new position. Your base salary will be determined based on your location, experience, and internal benchmarks. The base salary range is 100,000 - 140,000 CAD. You will also be eligible for equity and benefits.\n Our values are important. They are fundamental and lay the foundation for culture at Xanadu. Learn more about our values here .\n We are an equal opportunity employer and encourage candidates of all backgrounds to apply. We are committed to building an inclusive, safe, and equitable culture and fostering an environment where our employees feel included, valued, and heard. We are committed to meeting the needs of all individuals and support a barrier-free workplace. Should you require accommodations at any point during the recruitment process please contact Recruiting at [email protected] .\n Please be advised that we may use artificial intelligence (AI) tools to assist in the screening and assessment of applicants for this position. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.",
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    "title": "Photonics Engineer - Experimental Statistician",
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