Job Title

Who we are Nomad Atomics is on a mission to make the broad uptake of quantum sensing a reality and simultaneously push the limits of our field beyond what we think is possible. We are building the worlds most advanced fit-for-purpose quantum sensors to allow us to see the world like never before. Our team is made up of leaders in the quantum sensing field. We believe the time for commercial quantum sensing has come, and we are determined with making it happen. We are growing here at Nomad Atomics FAST. We are searching for people who want to finally take the commercial sensing game into the modern era of technology. Who you are You are a voracious learner, a problem solver, and a doer. You are fascinated by emerging technologies and excited help build a company with ground-breaking ideas. You are excited to operate at the forefront of technology development and be the first in the world to demonstrate the true capability of these world leading sensors. You have an innate attention to detail and enjoy the challenge of modelling real-world systems. If youre anything like us, you love a challenge and use your skills and creativity to solve anything that comes your way. Your role If you love building immaculate computational software in Python and have good mathematical acumen, this role may be for you. Working hand in hand with the Nomad ML & Analytics Team and the Geophysics Team, you will be the driving force that translates cuttingedge research and complex algorithms into a robust, scalable, and productionready analytics software. This is an exceptionally handson role for a skilled computational machine learning engineer who is passionate about building software that solves fundamental scientific challenges. The role requires a creative, outofthebox thinker, capable of independent work while also engaged with a multidisciplinary team to provide the best outcomes. You will be responsible for endtoend geophysical modelling development and will be engaged daily in tasks like: Collaborating with our ML & Analytics Team and geophysical subject matter experts to build, test, and maintain Nomad computational software and quantum gravity sensor data processing pipelines. Taking novel computational techniques and algorithm prototypes designed by our research team and engineering them into reliable, performant software modules. Building robust data ETL pipelines and software scaffolding. Developing comprehensive unit and integration tests to ensure the scientific accuracy and reliability of our codebase. Contributing to our DevOps and MLOps practices, including containerisation (Docker), CI/CD pipelines, and future deployments on cloud platforms (AWS). Working with our technology and deployment experts to build the software tools needed for highly efficient surveying techniques. Its not about specifically where you have come from nor what qualifications you have. What truly matters is that you are an impossibly fast learner and are passionate about building exceptional computational software. People with competitive applications could have skills and experience such as: Exceptional machine learning/computational software development skills in Python (required). A strong, demonstrated background in DevOps and MLOps, including version control (Git), CI/CD, API design, Unit testing, data and experiment tracking, and objectoriented programming (required). A strong quantitative intuition and the proven ability to translate complex mathematical concepts from domains like machine learning, signal processing, and statistical simulation into highquality, efficient code (required). Demonstrated experience with Python Libraries: Scipy, Numpy, JAX, Pytorch, Tensorflow, Matploylib, Plotly, PyMC, multiprocessing. 3+ years of professional experience in a computational software development or dataintensive role, OR a portfolio of personal projects that demonstrates an equivalent level of skill and a passion for building complex scientific software. A degree in a quantitative field such as Computer Science, Engineering, Physics, or Mathematics. Experience in applying machine learning techniques to solve realworld scientific or engineering problems. A demonstrated ability to effectively communicate complex ideas and problem solve within fastpaced team environments. A history of thriving in diverse environments that value honesty, open communications, and strong bonds between team members. You must be an Australian Citizen or a Permanent Resident. Nicetohaves Degree in Geophysics or experience in geophysical modelling/inversion techniques. A Masters or a PhD in quantitative methods. Familiarity with Bayesian Statistics. Familiarity with Docker, AWS and Linux. If you think youre right for the role, but dont have some of these skills, reach out wed love to talk anyway. The role is fulltime and based in Melbourne, Australia. We have the flexibility to work from home from time to time, but the inperson interaction with our tech and geophysical teams will be critical. We offer a competitive salary, employee share option package and opportunities for professional growth and advancement. #J-18808-Ljbffr